rafmacalaba/datause-encoder-data huggingface dataset:
-33-

Bringing together all lines of business, and as- a proportion of premium income and investment earnings<sup>1 6</sup> , commissions to agents were 4.5%, home and field office expenses were 7.0% and dividends to shareholders in joint stock companies were 2.4%. The total charge for the client would then be 13.9% plus retained earnings in 1991, assuming that the risk-adjusted investment return paid by the companies is in line with returns obtained by investing directly in the market.

Regarding the composition of costs in all lines of business, Wright (1992) reports that, as a proportion of 1989- operating expenses, commissions to brokers and agents were 41.5%, salaries, wages and other compensation were 26.9%, advertising expenditure was 1.4%, real estate costs were 4.4% and investment operations 11.0%.

More specific information was obtained on the annuity business, which is of direct interest to' pensions. However, the methodology is not comparable to that used for Chilean life insurance companies. In that case we started with the spread between annuity and bond yields. Here we use accounting data on profits. This data is more significant that in Chile since the annuity business in the United States has been established for long: Table 9 _Annuity Premiums and Charges in the United States_ (billions of current dollars and %)

||I|ndividual|s||Groups||
|---|---|---|---|---|---|---|
||1989|1990|1991|1989|1990|1991|
|Premiums<br>|49.41<br>|_53.67_<br>|_51-.67_<br>|_65.59_<br>|_75.40_<br>|71.92<br>|
|(1) Commissions|2.22|2.70|2.89|0.41|0.56|0.66|
|(2) General Expenses<br>|_1.55_<br>|1.71<br>|1.88<br>|1.65<br>|1.82<br>|1.93<br>|
|Total Expenses(1)+(2)<br>|3.77|4.41|4.77|2.06|2.38|2.59|
|(3) Accounting profit|||||||
|before taxes<br>|4.21|3.82|5.94|1.84|3-.78|<br>2.48|
|Total Charges on<br>|||||||
|Annuitants (1l.+(2)+(3)|7.98|8.23|10.71|3.90|6.16.|<br>5.07|
|Expenscs/Premiums<br>|7.6%<br>|8.2%<br>|9.2%<br>|3.1%<br>|3.2%<br>|3.6%<br>|
|T. Charges/Premiums|16.2%|15.3%|20.7%|6.0%|8.2%|7.1%|
|Average 1989-91||17.4%|||7.1%||

Source: American Council of Life Insurance, in private communication with Suzanne Stennock.

16 pm **16 Premimncome was 67.9% of thie su** of prenamings **of premiurm income anxd invesunltmeant nsi** in 1991. **91**
|**Table 3 Measure**<br>Category|**ment of Fiscal Needs by Servi**<br>Measurement Unit|**ce Category**<br>Per Unit Cost|Components of Adjustment Index|
|---|---|---|---|
|Primary and|population of school|the country's per capita|wage index = the ratio of teachers' wage level to the national average;|
|Secondary|ages (e.g, age 7-18)|public expenditure on<br>|rental cost index = the ratio of per square rental cost to the national average;|
|Education||primary and secondary<br>education|student disability index = the ratio of the percentage of students with physical disabilities to<br>the national average;<br>poor family index = the ratio of the percentage of students from low-income families to the<br>national average.|
|Health|total population|the country's per capita<br>public expenditure on|health price index = the ratio of health care cost to the national average;<br>infant mortality index = the ratio of infant mortality rate to the national average;|
|||health care|inverse life expectancy index = the ratio of national average life expectancy to life<br>expectancy in this region;<br>inverse population density index = the ratio of national average population density to that in<br>this region;|
|Transportation|total length of roads in<br>this region|the country's per capita<br>public expenditure on<br>transportation|wage index = the ratio of wage level to the national average;<br>grade index = the ratio of average road grade to the national average;<br>snow index = the ratio of annual snowfall to the national average;<br>inverse population density index = the ratio of national average population density to that in<br>this region;|
|Police and Fire|total population in the<br>region|the country’s per capita<br>public expenditure on<br>police and fire<br>protection|wage index = the ratio of wage level to the national average;<br>crime index = the ratio of per capita crime rate to the national average;<br>fire index = the ratio of per capita number of fires to the national average;<br>urbanization index = the ratio of proportion of population in urban areas in the region of<br>municipality to the national average;|
|Social Welfare|total population in this<br>region|the country's per capita<br>public expenditure on<br>social welfare|minimum wage index = the ratio of minimum wage level to the national average;<br>poverty index = the ratio of percentage of low-income population to the national average;<br>old age index = the ratio of percentage of old population (e.g., age 60 or above) to the<br>national average;<br>unemployment index = the ratio of unemployment rate to the national average;<br>disability index = the ratio of percentage of physically disabled people to the national<br>average;|
|Other services<br>_Source:_Barati and|total population in this<br>region<br>Szalai (2000), p.42.|the country's per capita<br>public expenditure on<br>other services|wage index = the ratio of wage level to the national average;<br>real cost index = the ratio of per square rental cost to the national average;<br>urbanization index of the region = the ratio of proportion of population in urban areas in the<br>region of municipalityto the national average;|

25
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<!-- Start of picture text --> Chart VIl<br>ACTUAL REAL I -YEAR-OEPOSIT RATES<br>-2 -<br>-3 -<br>-4Y<br>-5<br>-6<br>-7-<br>-5<br>-12-<br>-'3<br>el 512 83 54 as as 87 mB<br>Year<br><!-- End of picture text -->
- 9 -

Figure 4. Number of Bidders and Size of Projects <!-- Start of picture text --> 450<br>400<br>350<br>300<br>250<br>200<br>150<br>100<br>50<br>0<br>0 5 10 15 20<br>Number of bidders<br>Engineering cost estimate (million US$)<br><!-- End of picture text --> Source: Author’s calculation.

In our sample, 29 out of 44 electricity procurements were embedded with some auction mechanisms assessing technical elements substantially prior to price comparison. It is not surprising because electricity projects are complicated and need high technical capabilities from contractors. The figure includes the traditional two-envelope procedure and other staged process where bidders’ substantial responsiveness is evaluated first. In many cases, financial and experiential responsiveness is checked, and technical scores are calculated based on bidders’ proposals. At that stage, price bids may or may not be opened.<sup>11</sup> But if a bidder is disqualified due to technical reasons, his price bid will not be taken into consideration regardless of how much it is. Our sample reveals that the introduction of technical assessment would likely reduce the average number of bidders from 4.9 to 4.6. And the normalized average bid is higher when technical thresholds are established (Table 1). Nonetheless, the probability distributions of normalized bids show a mixed picture; relatively low bids look rather aggressive even with technical requirements imposed, possibly because of various interactive effects among competition, entry, quality and costs (Figure 5). This will be explored in the following sections.

<u>Table 1. Competition, Price Bids and Quality Evaluation</u>

||W|ithout tec|hnicalev|aluation|||Withtechnicalevalu|ation||
|---|---|---|---|---|---|---|---|---|---|
||Obs.|Mean St|d.Dev.|Min|Max|Obs.|Mean Std.Dev.|Min|Max|
|Number of bidders|15|4.93|2.89|2|12|29|4.59<br>3.67|2|18|
|Normalized bid|43|0.95|0.23|0.44|1.43|88|1.18<br>0.58|0.40|3.81|

Source: Author’s calculation.

11 In the typical two-envelope procedure, price bids are not opened until the technical evaluation is finished.
- 4.29 Have you ever been dissatisfied with the way that your elected representative behaves?

- 1 Most of the time

- 2 Some of the time

- 3 Rarely

- 4 Never

- 5 Would rather not say

- _[If possible, specify reason and add code:________________________]_

Local Regional National

- 4.30 Are there ways of holding him/her accountable?

- 1 Yes

- 2 No

- 3 Would rather not say

_[If possible, specify reason and add code:________________________]_ Local Regional National

- 4.31 Have you ever used these?

- 1 Often

- 2 Sometimes

- 3 Never _[Go to question 4.33]_ 4 Would rather not say _[Go to question 4.33]_

_[If possible, specify reason and add code:________________________]_ Local Regional National

- 4.32 If yes, did they work?

- 1 Yes

- 2 Some impact

- 3 Little impact

- 4 No impact

- 5 Would rather not say

_[If possible, specify reason and add code:________________________]_ 111
9 over the last several decades in that country, and the incidence of occupationa i lness Is far higher.' **l** Because of these caveats, about the most that can be said is that there is a great deal of cross-country variation in participation rates for older workers In transkion economles, as can be determined by an examination of the data from Table 3. Labor force participation rates of older persons tend to be higher here than the average for developed nations: for instance, in Poland 33 percent of the men age 65+ were In the labor force at the end of the 1980s, as compared to rates below 10 percent in France and Italy. A notable outlier is Hungary where only 3-4 percent of men and women age 65+ are employed. Only In Poland Is a trend identifiable, and here too it seems to be downward, particularly for the younger age groups (age 55-64).

# Explaining Eariler Retirement

What explains this trend toward earlier retirement? One widely held view emphasizes factors forcing or "pushing workers out of their jobs, while the opposing perspective contends that Opull" factors attract olderworkers into retirement (Intemational Labor Office 1989; Kohli and others 1991). This distinction Is obviously somewhat arbitrary, since for example the onset of poor health can "push" a worker out of his job, but also can make leisure more attractive thus "pulling" that worker into retirement. Despite this caveat, it is useful to classify evidence on these two hypotheses for descriptive purposes. Evidence on the "push" hvyothesis: This theory holds that people truly wish to remain employed at older ages, but are forced from their jobs by declining productivity and poor health, mandatory retirement and age discrimination, and structural shfits in labor demand.

Productivity and Health: Many believe that productivity falls and employee health deteriorates with age, leading employers to force out older employees when health problems strike. Indeed, many surveys report that when people are asked why they retire, poor health is a common response.5 Nevertheless, it Is difficul **t** o measure the independent effects of health problems on older persons' work behavior, and in many countries people feel a is socially acceptable to retire because of
35

# <u>References</u>

Adams, Jr., Richard. 1991. The Effects of International Remittances on Poverty, Inequality and Development in Rural Egypt. Research Report 86. International Food Policy Research Institute, Washington, DC.

- Adams, Jr., Richard.  1992.  “The Effects of Migration and Remittances on Inequality in Rural Pakistan.” Pakistan Development Review, 31, 110-133.

- Adams, Jr., Richard.  1995.  Sources of Income Inequality and Poverty in Rural Pakistan.  Research Report 102.  International Food Policy Research Institute, Washington, DC.

- Adams, Jr., Richard.  1998.  “Remittances, Investment and Rural Asset Accumulation in Pakistan.” Economic Development and Cultural Change, 47, 155-173.

Deaton, Angus. 1992. Understanding Consumption. Oxford: Clarendon Press.

- Deaton, Angus.  1997.  The Analysis of Household Surveys:  A Microeconomic Approach to Development Policy.  Baltimore:  Johns Hopkins Press.

- Glewwe, Paul and Jacoby, Hanan.  2004.  “Economic Growth and the Demand for Education:  Is There a Wealth Effect.”  Journal of Development Economics, 74, 33-51.

- Psacharopoulos, George.  1985.  “Returns to Education:  A Further International Update and Implications.”  Journal of Human Resources, 20, 583-604.

- Psacharopoulos, George.  1994.  “Returns to Investment in Education:  A Global Update.”  World Development, 22, 1325-1343.

Ratha, Dilip. 2004. “Enhancing the Developmental Effect of Workers’ Remittances to Developing Countries.” In World Bank, Global Development Finance, pp. 169-173. Washington, DC.

- Stahl, Charles.  1982.  “Labor Emigration and Economic Development.”  International Migration Review, 16, 868-899.

Stark, Oded. 1991. The Migration of Labor. Cambridge, MA: Harvard University Press.

- Stark, Oded, Taylor, J. Edward and Yitzhaki, Shlomo.  1986.  “Remittances and Inequality.”  The Economic Journal, 96, 722-740.

World Bank. 2004. Poverty in Guatemala. Washington, DC.
10 has to be selected: we opted for a caliper of 0.5, and found the results insensitive to the choice of caliper.<sup>23</sup> We compute standard errors for the facility impacts using bootstrapping.

It is standard practice in applications of PSM to limit comparisons to a subset of cases to ensure comparability. One approach is to focus on units lying on the common support of propensity scores. Our focus is on the effect of NCMS on the ‘treated’—i.e. the average treatment effect on the treated, or ATT. Given this, imposing the common support would entail excluding treated households with propensity scores that are larger than the maximum propensity score observed in the untreated group.<sup>24</sup> In this application, this would result in dropping relatively few treated households. A less ad hoc approach, and the one adopted in this paper, is that suggested by Crump et al. (2006): the sample is selected so as to minimize the variance of the estimated average treatment effects.

# IV. **DATA**

The analysis is based on panel data from 12 provinces.<sup>25</sup> The starting point for constructing the panel was the 2003 round of the National Health Service Survey (NHSS), administered by the Center for Health Statistics and Information (CHSI) of the Ministry of Health (MOH).<sup>26</sup> The NHSS collects data on, among other things, general household and individual characteristics, health status, use of health services, and health related expenditures. The 2003 NHSS covered approximately 54,000 households in 900 villages across all 31 province-level units, with counties, townships, villages, and households selected using a used a multi-stage stratified random sampling strategy.

A follow-up survey, in which households in the 2003 NHSS were re-interviewed, was implemented by the CHSI in the fall of 2005. This survey covered 10 counties that had begun piloting the NCMS in the intervening period since the 2003 survey was fielded and 5 that had not

> 23  Results are available on request.

> 24 If we also wanted to estimate the average effect of treatment on the untreated and the overall average treatment effect, the common support would also exclude untreated cases with a propensity score smaller than the smallest propensity score in the treated group. 25 Details on survey design and implementation, as well as extensive descriptive analysis, can be found in Center for Health Statistics and Information (2005; 2006). The former is available upon request from the authors. 26 The first NHSS was implemented in 1993, and it has since been implemented every five years.
indicates that the di¤erent determinants considered explain more than half of the variation in backward GVC participation shares across countries.

In Columns (2)-(6) of Table 1, we modify the baseline regression by including alternative or additional control variables or by changing the estimating sample. First, in Column (2) we replace exchange rate appreciation by a measure of misalignment whose e¤ect on GVC participation remains insigni...cant. Next, in Column (3) we include alternative measures of trade openness related to membership in PTAs (NAFTA, EU, MERCOSUR, ASEAN) and deep integration e¤orts. The estimated coe¢ cients show that countries’EU or ASEAN membership are linked to signi...cantly higher backward GVC participation shares. Third, to understand whether the patterns identi...ed are driven by a particular type of countries, we drop high-income countries as de...ned by the World Bank income classi...cation, from the estimating sample in Column (4).<sup>34</sup> This sample exhibits substantially less cross-country variation but several patterns identi...ed in Column (1) still hold, namely the strong negative impact of tari¤s and distance to GVC hubs and the strong positive impact of political stability on backward GVC participation. Fourth, we add as a proxy for non-tari¤ trade costs and connectivity a measure of the time to import in Column (5) and a control for the importance of females in the labor force in Column (6). The baseline results in Column (1) remain robust. We also include other control variables, such as the credit to GDP ratio, measures of the quality of logistics infrastructure, internet infrastructure, the prevalence of spoken English in the regressions, but these variables were all insigni...cant.<sup>35</sup> To understand which sectors within the economy are driving the aggregate results presented in Table 1, we estimate Equation (1) separately for each of the backward GVC participation measures by broad sector - agriculture, mining, manufacturing, and services.

> pass-through and disconnect observed in the data is due to the fact that large exporters are simultaneously large importers, with high-market-share and high-import-intensity.

> 34Since many countries change income status during our sample period, we use a time-varying World Bank income classi...cation to identify high-income countries.

> 35These results are available upon request. A di¤erent type of robustness checks uses GVC participation measures based on alternative TIVA and WIOD databases. These databases’time, and importantly, country coverage is much more limited than EORA’s, as they focus on high- and middle-income countries. Thus, the cross-country variation in GVC participation and in determinants is much smaller. But the broad patterns of results are similar to those in Tables 1 and 6 though weaker in signi...cance. The estimates that remain signi...cant for backward GVC participation are the negative impact of natural resource endowments, distance to GVC hubs and domestic industrial capacity and the positive impact of political stability.

17
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# I. Introduction

Theoretical models of the development process and actual plans for industrialization often assign a key role to trade policy measures. Moreover, in addition to the maintenance of steady growth in exports<sup>and</sup> accompanying increases in foreign exchange earnings, developing countries repeatedly stress the<sup>need to reduce their</sup> dependence on traditional primary product exports. Among the factors cited as the underlying<sup>reasons for this</sup> proposed shift are' (1) the purported deterioration in the terms of trade for primary commodities;<sup>(2) the substitution</sup> of synthetics for _many_ of these items (plastics for metals, artificial for natural fibers, chemical sweeteners<sup>for</sup> sugar); (3) the instability of primary product pxices in international markets; (4) the increased employment opportunities associated with the production and export of manufactures; and _(5)_ the realization of economy-wide linkages and *learning effects' resulting from the processing (manufacturing) function (see Helleiner<sup>and Welwood,</sup> 1978 or Roemer, 1979).

One method suggested for increasing the proportion of developing countries' trade in fabricated goods is to increase the processing of natural resource-based products now exported in primary form. However, a factor often cited as worling against efforts to increase domestic processing is the structure of tariffs and<sup>other</sup> trade barriers in major import markets. Specifically, zero or low tariffs are generally applied to industrial countries' imports of primary (unprocessed) commodities with the duties increasing, or 'escalating', as the product experiences increased fabrication. Tariff escalation has been acknowledged to produce a tmde bias against<sup>processed goods due</sup> to the higher import duties imposed on these items.' 'For example, Balassa (1968, p. 195) states that 'increases in nominal and effective duties from lower to higher stages of transformation point to the existence of discrimination against the processed<sup>export products of developing</sup> countries.- A similar position concerning the influence of escalating t- Yfs has been taken by<sup>Johnson (1965).</sup> Representative studies which document the existence of tariff escalation -a developed<sup>countries include UNCTAD</sup> (1968, 1980) and Yeats (1979). Yeats (1984) argues that a trade bias against processed commodities<sup>may occur</sup> even when there is no escalation in tariffs because of generally higher import demand elasticities<sup>for processed as</sup> oppo99d to primary commodities.