rafmacalaba/datause-encoder-data huggingface dataset:
13 administrations not too different from those of the EU countries. In theory, one could assume that all these countries had to do was to make copies of the tax laws of some EU country and make them their own. This, however, would be missing completely what tax reform is and how tax systems must be nested in the economy of a country. They must reflect the structural characteristics of a country‟s economy if they are to be successful. (...) Some of these changes are still taking place. Thus, in some ways, their tax systems have been adapting themselves to moving targets. It is to be expected that this process will continue for a few more years until the economies of these countries become fully market oriented, with characteristics, structures, and institutions similar to those of the other European countries” (p. xiv). This analysis complements the previous studies that have explored tax morale in the 1990s (Torgler 2003, 2007b, Frey & Torgler 2007).

# **III. EMPIRICAL APPROACH**

We explore the newest European Values Study (EVS) 2008 in conjunction with the data from 1999/2000. The EVS is a European-wide investigation of socio-cultural and political change. The survey collects data on the basic values and beliefs of people throughout Europe and is seen as the most comprehensive research project on human values in Europe. The EVS was first carried out from 1981 to 1983. The methodological approach is explained in detail in the EVS (1999) source book, which provides information on response rates, the stages of sampling procedures, the translation of the questionnaire, and field work, along with measures of coding consistency, reliability of data, and data checks. Country surveys are conducted by experienced professional survey organizations. Interviews were face-to-face and those interviewed were adult citizens aged 18 years and older. Clear guidelines are provided to guarantee the use of standardized information in the surveys and the national representativeness of the data. To avoid framing biases, the questions were asked in a
of socioeconomic status for the student and peers. First, I use parental education, defined as the average between the two parents when information for both is available. The four socioeconomic groups are defined in relation to levels attained: incomplete primary, complete primary, complete secondary and complete tertiary. For the regression testing the existence of heterogeneous effects, I compute the average years of education.<sup>16</sup> For reference, I also include in the tables the results using the variable books but only for observations for which there is also information of parental education. This is to help distinguish between difference in results arising from the use of alternative proxies of socioeconomic status and those from a smaller sample, given the presence of non-random missing values. The second proxy of socioeconomic status is based on assets and access to services at home. I construct an asset index as the first principal component of a factor analysis. The boundaries of the socioeconomic groups are such that the distribution of students is similar to that derived from the number of books, with 60 percent of pupils in the lower two groups.

Table 8: Robustness Analysis

||Heterogenous|Class composition|Co|mbined efect|s|
|---|---|---|---|---|---|
||increasing|not strictly monotonic|UM largest|L-LM vs U|UM vs U|
|Public schools|✓|✓|✓|✓|✓|
|Parental education|✓|✓|✓|✓|✓|
|Assets (PCA)|✓|✓|(✓)||✓|
|Math|✓|✓|✓|✓|✓|

Table 8 summarizes the results; details can be found in the Appendix. In all cases, the main conclusions remain. Crucially, they imply that increasing the degree of segregation of children on economic grounds will harm worse off students test scores while increase the attainment of richer pupils. In other words, the gap in performance would deteriorate. As mentioned before, the effect on the average test score is unclear. For this, I now turn to simulations.

> 16The original variable is expressed in terms of levels attained. I impute years of education using data from the Permanent Household Survey (October 2000). For incomplete level categories, I impute using the median value of the category, by province and gender.

25
Tatyana Bogomolova, Gregorio Impavido, Montserrat Pallares-Miralles same. The pension expenditure as a percentage of GDP is lower in the alternative baseline as fewer workers would accrue pension benefits. However, due to the fact that fewer workers would pay for pension benefits, the required contribution rate would be higher in the alternative baseline. Finally, the implicit pension debt would be much lower in the alternative baseline reflecting smaller growth of covered population.

**Table 10: The impact of lower covered population growth rates on end of simulation** **<u>period results.</u>**

|**Indicator**|**Govern**<br>**emplo**<br>|**ment**<br>**yees**<br>|**Teach**<br>|**ers**<br>|
|---|---|---|---|---|
||Alternative<br>baseline|Main<br>baseline|Alternative<br>baseline|Main<br>baseline|
|Dependencyrate|56%|35%|45%|41%|
|Replacement rate (reduced<br>pensiononly)|69%|68%|72%|70%|
|Expenditure as % ofGDP|0.5%|2.2%|1.5%|2.3%|
|Required contribution rate|62%|38%|56%|44%|
|Implicit pension debt as % of<br>GDP|8%|46%|29%|52%|

**Source** : WB calculations based on PROST.

# **V OPTIONS FOR REFORM**

Two reform options have been modeled as part of the study, with some variations within each reform scenario. In the first option the PSPF scheme is transformed into a provident fund (a scenario now being considered by the Government). We will further refer to this option as “Reform I”. The second option entails transforming the PSPF scheme into a hybrid scheme with a small defined benefit component and a complementary mandatory defined contribution component. We will further refer to this reform option as “Reform II”. Both reforms substitute wage indexation of benefits with price indexation for switchers<sup>18</sup> .

A number of variations for each of each reform scenario have been modeled. The first pair of variations relates to the switching pattern of workers with accrued pension rights: we consider the two polar cases of immediate switching of all current workers to the reformed scheme and grandfathering of all workers with accrued rights in the unreformed scheme. In addition, in the provident fund reform option (reform I), we consider two cases of benefit indexation for non switchers: maintaining wage indexation or changing it to prices. In the case of the hybrid reform option we do not explore price indexation for non-switchers.

Another pair of meaningful variations involves assumptions regarding the interest rate earned on individual accounts. For each reform I and II we model two cases where assets are well managed or mismanaged.

Hence, seven cases will be analyzed in this section and they are labeled as follows:

> 18 Here and further in the text switchers mean those individuals who switch to the reformed scheme and non switchers – those who stay in the unreformed scheme.

- 48 -
accounted for room and board while the HDB figure included the full treatment. To illustrate, in 1990, an appendectomy involving a five-day stay cost an average of USD400.00 in the private sector when doctor's fees and hospital hotelling and pharnacy charges were factored in. At HDB, the cost of an appendectomy was USD56.88 (USD11.38*5) in 1990, 14% of the fee charged in a private sector hospital of equivalent quality. By 1997, cost of care at HDB had gradually increased to an average of 50% of private sector care.

**Table 5.1. Comparisons of HDB Fees with Average Third-Class Private Sector Rates in 1990 and 1994.30**

|________<br>________|**HDB/ALS**<br>**M Rates**<br>**1990**|**|Averi**<br>**l**<br>**S**<br>**..**|**_.H*_**_I_<br>t 41||
|---|---|---|---|---|
|**Outpatient Ca**|**re**||||
|Minor surgery|11.38|14.00|K<sup>3</sup><br>1+12.14|36.00|
|Minor surgery<br>(emergency room)|5.69|25.00|K + 6.079<br>15.18""|20.00|
|Plaster service|5.69|25.00|9.11|20.00|
|Emergency<br>consultation|2.28|16.70|4.86|22.28|
|Regular consultation|1.14|12.50|4.86|16.5|
|X-ray|1.14|14.00|R" =0.12|16.00|
|E.C.G.|1.14|12.00|3.04|15.00|
|Laboratory|_0.57_per<br>analysis|2.00*<br>l17.00-25.00**||L<br>= 0.08<br>l|3.30*<br>25.00-37.00**|
|**Inpatient Care**|||||
|Medical Ward||12.50/Day***|15.18/Day|22.00/Day***|
|Maternity Ward|5.69/Day|12.50/Day***|18.21/Day|22.00/Day***|
|Newborn nursery||10.00/Day***|6.07/Day|15.00/Day***|
|Surgery|11.38/Day|12.5/Day***|K = 1.21|22.00/Day***|
|Gynecology||12.5/Day***|15.18/Day|22.00/Day***|
|Intensive Care|11.38|60.00/Day***|15.18/Day|100.00/Day***|

All figures are in US Dollars, converted using the exchange rates of the respective years. In 1990 the Lebanese Lira was 879.00 to the US Dollar. In 1994, LL1647.00 = One USD. In 1999, LL1508.00 = One USD. Exchange rates were obtained from the Central Bank of Lebanon, courtesy of Youssef El-Khalil. * Minimum cost per single test.

** Range for standard pre-operative/diagnostic tests.

*** Figures are for room and board only.

0 Fee if operation was carried out by surgeon. '1 Fee if operation carried out by intern or resident.

Rs (for _Radiologie)_ and Ls (for _Laboratoire)_ are set and used in the same way as Ks. Different x-ray and lab procedures have different R and L values.

Source: Author's construction combining data from HDB and MedNet Liban.<sup>32</sup>

> 30 In private sector hospitals, the cost of second-class service (B) is equivalent to the cost of thirdclass service (C) + 60%. First class service (A) = C + 180% (MEDNET estimates).

3 1 The K system is determined by the Social Security Administration and the Lebanese Order of Physicians. It classifies each medical procedure as being equivalent to a certain number of Ks (for each of three classes of service). The idea behind the system is to achieve some consistency and equity in billing and remuneration for health care. For example, a third-class appendectomy and normal delivery are valued at 50K for all hospitals, throughout the country. Today the third-class K is valued at LL8,000 (USD5.30), and the scales are updated periodically.

20
Surviving Firms of the Syrian Arab Republic – A Rapid Assessment<sup>1</sup>

# Background

In early 2017 the World Bank undertook an Economic and Social Impact Assessment of the conflict in the Syrian Arab Republic. This resulted in the report _The Toll of War: The Economic and Social Consequences of the Conflict in Syria._ As part of the research initiated during this work, a rapid survey of Syrian enterprises was commissioned to understand the experiences and challenges of the private sector in Syria, with the intent of contributing to the World Bank’s ongoing efforts to understand the socio‐economic effects of the conflict in Syria.

The results of this survey are detailed in this paper and represent, as far as we know, the only countrywide survey of Syrian enterprises since the crisis began. The survey was conducted by phone, using as a sample the list of firms surveyed in the World Bank enterprise survey conducted in 2009 which included 508 manufacturing and services enterprises in six areas of the country: Aleppo, Damascus city, Damascus countryside, Hama, Homs, and Latakia.

Of the 508 firms surveyed in 2009, 203 ‐ or 40% ‐ could not be reached at all. This paper analyzes the patterns emerging among those missing firms, as well as the surviving firms, and discusses what conclusions may be drawn from the data collected on their problems, constraints, and current activities.

This paper examines the primary effects reported by businesses as a result of the conflict. Establishing basic services like electricity, fuel, water and gas emerge as key constraints in most of Syria. However, the bigger challenge that emerges from this study is the devastating loss of life and massive migration of people. Businesses across Syria report loss of skilled workers, managers, and unskilled workers as well as supply chain relationships as a ubiquitous effect of the war. The key conclusion of this analysis is that the damage to social and human capital is significant, and rebuilding that social and human capital is likely a greater challenge than the bricks and mortar.

# Discussion of the sample, methodology, and missing firms

It was extremely challenging to conduct a firm survey in Syria in early 2017 due to the ongoing insecurity across the country. For this reason, the survey was conducted by phone. The survey was designed to be completed in approximately 30 minutes and the questions focused on changes that firms have experienced since the beginning of the crisis in 2010. The questions covered the following topic areas: major problems and constraints to firms, sales, supplies and costs, finance, and employment. (See Annex B for the questionnaire.) The survey was designed as a follow‐up to the 2009 Enterprise Survey of Syria. The 2009 survey included 508 firms and the 2017 survey attempted to re‐survey all 508 firms which were surveyed in 2009. Table 1 below provides a breakdown of the response outcomes for

> 1 This paper and the supporting analysis was undertaken by Nabila Assaf, Kinley Salmon, and David C. Francis based on a survey conducted in April and May 2017.

2
decrease of approximately 13.3 percent of the mean, while the value for lower wage employment is around 8.6 percent of the mean. Table A17 in the appendix presents the same regression results, but without the heteroskedasticity correction. The signs of the coefficients are generally similar, but some change in magnitude. The most obvious change is the coefficient on above upper secondary for formal wage employment; while still positive, it is much smaller in magnitude.

Table 6: Urbanization and jobs ladder (All countries)

||(1)<br>Upper tier<br>Informal<br>self-emp.|(2)<br>Formal<br>wage|(3)<br>Upper tier<br>informal<br>wage|(4)<br>Lower tier<br>informal<br>wage|(5)<br>Lower tier<br>informal<br>self-emp|(6)<br>Unemployed|(7)<br>Inactive|
|---|---|---|---|---|---|---|---|
|Urban pop. (log)|-0.037|0.050|0.025|0.047|-0.127|0.060**|-0.017|
||(0.049)|(0.141)|(0.020)|(0.083)|(0.125)|(0.029)|(0.098)|
|Rural pop. (log)|-0.055**|-0.189**|0.002|0.028|0.183*|-0.027|0.059|
||(0.023)|(0.073)|(0.011)|(0.066)|(0.097)|(0.031)|(0.113)|
|GDP p.c. (log)|0.023|0.187*|0.010|-0.025|-0.108|-0.010|-0.077|
||(0.027)|(0.096)|(0.010)|(0.037)|(0.077)|(0.020)|(0.047)|
|Observations|466|466|466|466|466|466|466|

Notes. Standard errors are in parentheses and are clustered at the country level. Country and year fixed effects are included in all specifications. The proportion of people with primary education or less is the omitted category. Shares refer to all workers with non-missing firm size. * p<0.10 ** p<0.05 *** p<0.01.

We now turn to the relationship between changes in the job ladder and urbanization and population growth. Table 6 presents the results of the regressions based on equation (3) separating population into urban and rural population. There are three key coefficients worth noting. First, higher levels of urban population are modestly correlated with higher levels of unemployment. This is reminiscent of the recent work exploring the relationship between urban unemployment and the unskilled population (S. Feng et al., 2017), though we note that we do not find the same negative relationship between GDP and unemployment as others (Y. Feng et 28
appears to be crucial for its success as indicated by the inconsistent results obtained when, as in columns 1 and 2, Vietnam veteran status is not controlled for.<sup>28</sup>

# **_4.3 Interpretation of the Instrumental Variables Estimates of the Effect of College Education on Smoking_**

The instrumental variable strategy implemented in this chapter uses the fact that college enrollment as a draft avoidance strategy during the Vietnam War era provides a plausibly exogenous variation in educational attainment. During the Vietnam War, going to college was associated with an additional benefit: avoiding the draft and the disutility associated with it. This additional benefit induced some individuals that would otherwise not have enrolled in college to enroll.

It is however likely that the individuals induced to enroll in college because of the Vietnam draft were not random among the group of individuals who, in the absence of the draft, would not have gone to college. On the contrary, it is reasonable to expect that those males who decided to enroll because of the draft were the ones who were close (just under) to the margin of going to college. The possibility to avoid the draft if they were in college made them switch and decide to enroll in college. Typically, the “switchers” would have a lower discount rate (i.e., a larger β) than the individuals who did not enroll, despite the extra benefit of draft avoidance, but a higher discount rate than the ones who would have gone to college even in the absence of the draft.

It then follows that, if there is heterogeneity in the returns to schooling, the instrumental variable estimate obtained is not a consistent estimate of the average effect of education on smoking in the population (Card 1995, 2001; Heckman, Lalonde, and Smith 1999). The instrumental variable estimate should rather be interpreted as the effect of education for the subgroup of males that has been induced to enroll in college in order to avoid the Vietnam Draft. Imbens and Angrist (1994) define this estimator as the local average treatment effect (LATE).

This qualification in the interpretation of the results is important, as it does not permit generalizing the estimates obtained from the instrumental variable estimates for the entire population. However, an estimation of the effect of education on smoking for those individuals who are at the margin between going to college or not is interesting from a

> 28 However, since the first stage of the instrumental variable strategy implies that it was possible to avoid, or at least to delay,  the draft by staying in college, it might be argued that Vietnam veteran status is endogenous. To address the issue of the potential endogeneity of veteran status, I would need an additional instrument for veteran status. I am investigating the feasibility to use height and congenital medical conditions available in some of the National Health Interview Surveys, as those physical characteristics, associated with a higher probability of failing the physical induction test in the army, might be an exogenous determinant of the likelihood to be a Vietnam veteran.

16
# **Are Microcredit Participants in Bangladesh Trapped in Poverty and Debt?**

## **1. Introduction**

Microfinance has succeeded in reaching the poor and women who lack access to mainstream financial institutions.<sup>1</sup> But its success in reducing poverty, a stated goal of microcredit programs, is less certain. The microlending system has created such innovations as group liability enforcements and dynamic incentives, claiming that many of the poor, including women and other vulnerable groups, could be lent to profitably, and beneficiaries could accrue both short- and medium-term welfare gains. But critics argue that, while microfinance may satisfy the unmet financial demand of the poor, the accrued gains in income and consumption may not suffice to affect poverty reduction or asset accumulation in a sustainable way.

There are two strands of empirical literature on the poverty reduction role of microcredit. The first strand of studies, which uses non-experimental research methods, observes that microcredit helps to promote social, human, and economic development in various ways (e.g., Dunford 2006; Hossain 1988; Shaw 2004; Panjaitan-Drioadisuryo and Cloud 1999; Chemin 2008; Khandker 1998, 2005; McIntosh 2008; Pitt and Khandker 1996, 1998; Pitt, Khandker, McKernan, and Latif 1999; Kevane and Wydick 2001; Imai, Arun, and Annim 2010; Boonperm, Haughton, and Khandker 2009).<sup>2</sup> A recent study, using panel data from 1997 to 2005, finds that larger benefits are realized from medium-term, rather short-term, participation (Islam 2011). Another study, using a long panel survey (1991/92–2010/11), also confirms that participants who remained with

> 1 According to the Consultative Group to Assist the Poor (CGAP), there are more than 200 million beneficiaries of microfinance worldwide.  In Bangladesh alone, about one-fifth of the country’s 150 million people—including threefifths of rural households—are members of microfinance institutions.

> 2 On the other hand, several studies argue that women have no control over the obtained credit and thus do not benefit from program participation (Amin and Pebley 1990; Goetz and Sen Gupta 1996; Mahmud 2003).

2
all below 20 percent. Honduras exports only 7 percent of total output in the textiles sector, and 10 percent of the total production of food, beverages, and tobacco. Recall that the previous section identified these sectors as the only ones facing significant trade barriers in the US market, which implies that it would be difficult for Honduras to take full advantage of higher export prices in the US without significant changes in its export intensities.

Table 5: Sectoral Composition of Production, Exports, and Imports, 2004 <u>(Percent)</u>

|Sector|Share in|Exports to|Imports|Share|of tota|l value|added|
|---|---|---|---|---|---|---|---|
||total pro-<br>duction|total pro-<br>duction|to total<br>demand|Unsk.<br>labor|Skil.<br>labor|Ter.<br>labor|Cap.+<br>land|
|Bananas|1.3|95.0|2.4|0.6|0.2|0.5|98.7|
|Cofee|2.1|98|11.6|25.3|0.1|0.8|73.8|
|Sugar|1.2|14.5|2.5|0.2|0.3|0.0|99.5|
|Mining|1.1|56.4|0.2|3.9|2.9|3.4|89.9|
|Livestock|4.2|0.2|2.7|25.8|0.0|1|73.2|
|Wood|0.9|76.9|48.3|0.2|0.0|3.1|96.6|
|Non-traditional crops|4.6|43.8|34.1|10.1|0.7|9.1|80.1|
|Domestic crops|6.9|2.1|19.9|68.2|7.8|5.2|18.7|
|Oil|0.0|0.0|100.0|0.0|0.0|0.0|0.0|
|Food, beverages, tobacco|11.6|10.2|9.1|71.2|9.8|0.1|18.9|
|Textiles|6.4|7.0|14.1|0.6|76.0|12.7|10.6|
|Paper|2.1|11.2|39.2|76.8|0.9|0.1|22.1|
|Chemicals|2.5|10.4|49.2|0.8|0.4|68.4|30.4|
|Metals, minerals, mach.|1.4|59.6|92.9|0.7|1.9|47|50.3|
|Other manufacturing|4.6|19.5|61.3|0.5|64.2|21.6|13.7|
|Electricity, water, gas|1.3|1.5|11.5|0.3|0.1|0.8|98.8|
|Construction|6.3|0.0|3.0|43.8|20.0|10.7|25.5|
|Other services|35.1|31.8|25.4|30.0|25.0|18.7|26.4|
|Public sector|12.8|0.0|0.0|34.6|23.1|42.4|0.0|
|Total|100.0|44.0|30.7|34.8|22.3|17.9|25.1|
|Agriculture|21.2|60.1|18.5|42.3|4.5|6.1|47.2|
|Manufacturing|29.6|30.1|47.3|42.2|26.3|12.0|19.5|
|Services|42.7|52.3|21.3|31.9|23.6|20.9|23.6|
|_Note:_ The manufacturing aggre<br>domestic consumption and exp<br>and imports.<br>_Source:_ Author’s calculations u|gate includes <br>orts. Total de<br>sing data from|oil and mining. <br>mand includes <br> the SAM.|Total produ<br>demand for d|ction inclu<br>omestical|des prod<br>ly produc|uction for<br>ed goods||

Import dependence is under one-third of total demand for the economy overall, and is significantly lower in the farm sector. The earlier section highlighted the potential vulnerability of farmers to trade liberalization under DR-CAFTA since Honduras sources a large share of its agricultural imports from the US. However, Table 5 shows that, with the exception of wood and non-traditional crops, most farm activities are under moderate competitive pressure from imports.<sup>15</sup> One reason for the low penetration of foreign-produced farm goods is the relatively higher protection afforded

> 15The import dependence of the wood sector is close to one-half of total demand, but its share in total output is very small relative to other agricultural activities. Although the import dependence of domestic crops is not large relative to the economy-wide average, import dependence of one-fifth is not small in absolute terms. For example, it

12