rafmacalaba/datause-encoder-data huggingface dataset:
# 3 Data and methodology

## 3.1 Description of the data

The data set consists of an unbalanced panel of annual observations for a group of developing and transition countries, covering the period, 1970-2014.<sup>2</sup> The data for exchange rate regimes is based on the Reinhart and Rogoff de-facto exchange rate regime (COARSE) classification, the current account data is from UNCTADStat database, eurodollar deposit rate is from the Federal Reserve System database, and the dataset for remittances and all other variables is from the World Bank’s World Development Indicators (WDI) database.<sup>3</sup> Table 1 presents a description of the exchange rate regime classification scheme. The applicable exchange rate regimes for this analysis vary between categories 1 and 5, with an increase in the index indicating a movement towards a more flexible exchange rate regime.

Table 2 shows descriptive statistics for the data on the main variables used in the analysis. As pertains to the variables of interest, current account as a percentage of GDP has a mean value of -4, but ranges between -44.7 and 50. Remittance receipts amounted to about 3.5 percent of GDP on average, and GDP per capita varies across countries over the sample period, ranging between US$219 and US$5665, with a mean of about US$1680. Table 3 presents correlation coefficients for remittances and the current account across the five exchange rate regime classes. Each regime class, with the exception of regime 3, shows a negative correlation between remittances and the current account. The estimates further show that when the regime classes are categorized into two groups only, as well as when the entire sample is considered, the correlation coefficient is negative in all cases.

Figure 1 presents a plot of the variation in remittances (% of GDP) and current account (% of GDP) in the Philippines and El Salvador between 1980 and 2013. Remittances as a percentage of GDP reached a peak of 13% in 2005 for Philippines, whereas the peak is 19% in 2006 for El Salvador. The current account as a percentage of GDP was at its lowest, -8%, in 1982 for Philippines, and -22% in 1981 for El Salvador. For both countries, there is not a clear pattern on how remittances relate to the current account. However, the graph shows that between 1999 and 2005, remittances

> 2 The selection of countries in the sample and the coverage period was on the basis of data availability.

> 3 Trade openness is measured as the sum of exports and imports expressed as a share of GDP.

5
# **The Welfare and Productivity Effects of Transit Improvements in Amman**<sup>*</sup>

Tatjana Kleineberg Sally Murray Yulu Tang World Bank World Bank Harvard University Jon Kher Kaw World Bank

## JEL Classification: R13; R32; R40; R52

Keywords: Urban Transport; Urban Land; Urban Productivity; Urban Jobs; Amman; Jordan; Spatial Computable General Equilibrium Model

> *We would like to thank Hogeun Park, Myriam Ababsa, and the World Bank transportation team for data and their expert reviews and comments. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.Contact: Development Research Group, World Bank, 1818 H Street NW, Washington, DC 20433. Email: smurray2@worldbank.org; tkleineberg@worldbank.org.
**Table 4.11 Employment by Sector and Gender, 2000**

|**Industries**|**Tota**|**l Workers**|**Female Workers**|**Long Term contract**|
|---|---|---|---|---|
|Manufacturing|Mean|**144**|**93**|**74**|
||Minimum|2|0|0|
||Maximum|3,300|2,100|1,594|
|Other industry|Mean|**59**|**7**|**18**|
||Minimum|3|0|0|
||Maximum|434|64|85|
|Services|Mean|**33**|**11**|**26**|
||Minimum|2|0|0|
||Maximum|1,420|682|1,397|
|Total|Mean|**78**|**42**|**44**|
||Minimum|2|0|0|
||Maximum|3,300|2100|1594|

Source: World Bank Survey, 2001 34. **Education** . The private sector attracts the higher end of the workforce, in terms of education. The majority has at least a high school diploma and less than 10 percent of shop floor workers did not graduate elementary school. By contrast, only 17 percent of Vietnam’s labor force finished high school and up to 50 percent has not finished elementary education.

35. Workers in the service sector are relatively higher educated than workers in the industrial sector. The majority of manufacturing workers have either a elementary or high school education. The level of education of private sector workers is also higher in urban areas than in rural areas. This may be due to the higher concentration of educated workers in urban areas, but also the result of a higher incidence of service activities.<sup>26</sup>

**Table 4.12 Mean Level of Education for Shop Floor Workers, 2000**

|||**Percentage**<br>|**of Workers wit**<br>|**h...**<br>|
|---|---|---|---|---|
|**Industries**|**College**<br>**Degree**|**High School**<br>**Diploma**|**Elementary**<br>**School**|**Not Yet Finished**<br>**Elementary School**|
|Manufacturing|10.7|49.0|28.9|11.6|
|Other industry|23.8|38.0|27.0|11.2|
|Services|32.0|48.3|16.1|3.5|
|Total|23.2|47.8|21.9|7.2|
|Total Labor|1|7.0|33.0|50.0|
|Force|||||

Source: World Bank Survey, 2001 36. **Wages.** The average monthly wage of shop floor workers is VND 720,000 in the manufacturing sector and about 920,000 in the service sector.

> 26 The VLSS 97-98 showed how the share of people with higher qualifications is increasingly concentrated in urban areas, leaving rural areas without strong educational or technical expertise.

18
3 In addition, our previous study in Tanzania, the RESPECT trial (“Rewarding STI Prevention and Control in Tanzania”) examined the effect of two different conditional cash transfer amounts ($10 and $20 USD) on risky sexual behavior. Cash transfers were offered every four months conditional on negative test results for a set of curable STIs. We found that offering cash awards of $20 USD resulted in a significant decrease in STI prevalence after one year, while there was no effect in the $10 USD group.<sup>16</sup> We conducted a pilot study to test this approach among FSW in Tanzania and found that providing cash conditional on negative STI tests was an acceptable and feasible approach in this population, however we were not powered to detect differences in incident infection and did not examine HIV.<sup>17</sup> Building on this evidence, we sought to examine whether conditional financial incentives are effective in reducing risk of HIV and STI infection among a larger sample of FSW.

The RESPECT II trial investigated the effect of lottery-based financial incentive intervention on the combined incidence of HIV and HSV2 among 2,206 FSW in Dar es Salaam, Tanzania over 2018-2022. The objective of our study was to understand whether a low-probability, high-reward incentive scheme offering a 100,000 TZS ($50 USD) reward to randomly selected lottery participants conditional on negative STI results could improve HIV and STI outcomes among FSW.

# **METHODS**

_RESPECT II study design and participant selection_ The “Rewarding STI Prevention and Control in Tanzania” (RESPECT II) study was designed as a two-arm parallel randomized controlled trial, with individuals as the unit of randomization. FSW were recruited using respondent-driven sampling (RDS), a chain referral sampling method designed to recruit hard-to-reach and hidden populations. Ten FSW who had previously assisted with intervention studies (and who were not themselves enrolled in our study) were trained in outreach and each recruited five FSW who served as the initial enrollees and as “seeds” for further recruitment. These ten FSW were identified through local health staff working with the FSW community and were selected to represent FSW in areas of Dar es Salaam with high sex work activity. Seeds were then given three coded coupons to recruit their peers into the study from various venues (bars, brothels, street); each participant who successfully enrolled in the study was then herself given three coupons to recruit additional peers into the study, with this process continuing until the desired sample size was achieved. Seeds and participants who helped with subsequent recruitment were given 4,000 TZS (approximately $2 USD) for each of up to 3 eligible FSW that were recruited. Fingerprint scanners were used to prevent multiple registrations across
prioritized projects for each village. The following sections provide further information on the sources of data on _ex-ante_ project preferences (III.1); selection process (III.2); selection outcomes (III.3); and villagers‘ satisfaction (III.4).

# IV.1. **Ex-Ante Project Preferences**

Data on _ex-ante_ preferences come from a survey administered prior to village council elections and project selection. In each village, the survey was administered to three groups of villagers: (1) ten randomly-selected male heads-of household; (2) a focus group of male village leaders; (3) a focus group of leading village women. The overall number of respondents surveyed exceeded 13,000 (see Table 2 for more detailed information).<sup>9</sup>

## [TABLE 2 HERE]

A question in the survey asked all respondents to indicate, from a list of potential projects, the three projects that should be implemented if the village was provided with a $60,000 grant.<sup>10</sup> From this data, we construct village-level dummy variables indicating the project most frequently preferred by each of the three groups,<sup>11</sup> providing measures of the preferences of male villagers, male elites, and female elites, respectively.

## [TABLE 3 HERE]

Table 3 presents the preferences for the three groups of villagers. Drinking water projects are the first choice of male household respondents and female elites, while preferences of male elites are more evenly distributed across different projects. A comparison of villages assigned to different

> 9 We did not administer the baseline survey to a random sample of female villagers due to financial and logistical constraints, so we do not have information on their preferences.

> 10 Male and female focus group respondents were asked to identify one project from a list of 15 possible projects, while individual male household and female respondents were asked to select and prioritize three projects from the same group of 15. To ensure comparability, we focus on the project that was named as the most important in the household and individual surveys. Female respondents were asked the question twice in both the group setting and individually, but we use only information from the female individual questionnaire and check robustness with the female focus group. To increase statistical power in the analysis, we group the 15 possible project types into five categories: (i) roads and bridges; (ii) irrigation; (iii) drinking water; (iv) electricity; and (v) other (which include men's courses, health courses, schools, health facilities, seeds, agricultural equipment, livestock, microfinance programs, communal toilet facilities, and community centers). The four types of projects not included in the “other” category are the four most popular types of selected projects.

> 11 In the event of two or more projects having the same number of respondents preferring them and these numbers exceeding the number of respondents preferring other projects, the respective projects were all marked as the most preferred.

9
**Table 10: Export growth has been led by light manufactures**

||Estimated<br>average annual<br>real growth<br>1992-97 (%)|Share in total<br>Exports in 1992<br>(%)|Share in total<br>Exports in 1997<br>(%)|
|---|---|---|---|
|Total exports|18.8|100|100|
|Agriculture|11.1|49.5|35.3|
|Heavy industry and minerals|12.3|37|28|
|Light Industry|45.1|13.5|36.7|
|_Of which:_||||
|-textiles and garments|||16.4|
|-footwear|||10.6|

_Source:_ World Bank (1998), GSO (various) and General Department of Customs _Note:_ Row 1 is estimated by converting exports in current US$ from GSO (1998) to constant Dong by using exchange rates from World Bank (1998) and the GDP deflator from GSO (1998).

This performance in manufacturing exports was supported by foreign investment. Vietnam's trade and taxation regimes now contain special provisions that allow exportoriented foreign enterprises to import duty free intermediate goods from abroad and to enjoy preferential tax rates. In addition, many joint ventures are also exempted from import duties on equipment goods, machine components, spare parts, and transport equipment and materials (CIE, 1998). Table 11 shows that the dollar value of exports by foreign invested companies - about 40% of which stem from light manufacturing- has grown by 80% per year between 1992 and 1997 (albeit from a small base). This has raised the share of exports by foreign invested companies from less than 4% to almost 20% of total exports in 1997.

**Table 11: FDI accounts for a growing share of Vietnam's exports**

||1994|1997|
|---|---|---|
|Total exports by foreign<br>companies ($ million)|161.1|1,790|
|Total light industrial exports by<br>foreign companies ($ million)|n.a.|728|
|Share of FDI in total exports (%)|3.9|19.5|
|Share of FDI in light industry exports**(%/O)**|n.a.|21.6|
|_Source:_Line 1, and 3 GSO, line 2 and 4 estima|tion from M|PI data|

The Asian crisis has interrupted these encouraging trends. In 1998, foreign direct investment to Vietnam fell from $2.0 billion in 1997 to less than $800 million, with an estimated decline of $612 million in light industry (IMF, 1999). As can be seen in table 12, in 1998 real manufacturing export earnings grew by less than 1%. Had light manufacturing exports earnings continued to grow at their five years average pre-crisis rate of 45% per year, Vietnam might have exported an additional $1.2 billion of light manufacturing exports in 1998. Fortunately, table 12 also shows that as far as manufacturing exports are concerned Vietnam is recovering from the worst impact of the crisis. In the first 8 months of 1999, total exports have staged a strong come back. And while the decline in agricultural prices on world 11
Table 6: cross-sectional 2SLS

|equation no.|(1)|(2)|(3)|
|---|---|---|---|
||OLS|First stage|Second Stage|
|cumulative PSG conditions 1996-2008|.0002<br>(.002)|.|.011<br>(.005)<sup>_∗∗_</sup>|
|CPIA 1996|-.710|1.388|-.739|
||(.044)<sup>_∗∗∗_</sup>|(1.874)|(.049)<sup>_∗∗∗_</sup>|
|average annual GDP per capita growth|.0009|.064|.002|
||(.010)|(.108)|(.009)|
|log of GDP per capita 1996|.100|-1.601|.173|
||(.049)<sup>_∗∗_</sup>|(3.410)|(.074)<sup>_∗∗_</sup>|
|Political Rights 1996|-.111|-1.209|-.100|
||(.024)<sup>_∗∗∗_</sup>|(1.059)|(.026)<sup>_∗∗∗_</sup>|
|change in Political Rights|-.122|.419|-.115|
||(.027)<sup>_∗∗∗_</sup>|(1.495)|(.029)<sup>_∗∗∗_</sup>|
|ethnic fractionalization|-.043|2.261|-.125|
||(.196)|(6.240)|(.190)|
|average annual aid over GDP|-1.231|38.570|-.009|
||(1.101)|(60.350)|(1.219)|
|cumulative agri. conditions 1996-2008|.|1.194<br>(.536)<sup>_∗∗_</sup>|.|
|log of 1996 population|.|4.721<br>(1.696)<sup>_∗∗∗_</sup>|.|
|No. observations|126|126|126|
|_R_<sup>2</sup>|.681|.247|.575|
|F test of excluded instruments|.|10.613|.|
|_p-value_|.|0.0001|.|
|test of endogeneity|.|.|9.56685|
|_p-value_|.|.|0.002|
|Overidentifcation test|.|.|.006629|
|_p-value_|.|.|0.9351|

Note: Dependent variable is the change in policy quality over the period 1996-2008, as measured by the CPIA cluster D average. Robust standard errors in parentheses. * significance at 10%; ** significance at 5%; *** significance at 1%.

38
We find that in all cases the quintile 1 interaction term coefficient falls within the 95 percent confidence interval of the coefficients generated in the partitioning exercise. Furthermore, whenever the interaction term coefficient is statistically significantly different from zero in Tables 4 to 7, the 95 percent confidence interval of the coefficients generated in the partitioning exercise does not include a coefficient of zero or of the opposite sign.

We therefore conclude that our main results are not mechanically driven by idiosyncratically low repayment among some control farmers in certain localities.

# **6.2 Evidence for a Reduction in Ex-Post Moral Hazard**

Reductions in ex-ante moral hazard may help encourage higher loan repayment by improving farm output so that farmers have higher incomes with which to make loan repayments. Reductions in adverse selection – reduced loan sizes for the “bad” borrowers – also help increase repayment performance. But a question that remains is whether any of the increase in repayment is due to reductions in _ex-post_ moral hazard. In other words, are there reductions in strategic or opportunistic default by borrowers, holding constant loan size and farm profits?

We investigate this by running regressions where repayment outcomes are the dependent variables, but where we include as independent variables in the regression controls for agricultural profits and the total originally borrowed. Results are reported in Online Appendix Table 15.<sup>25</sup> The profits and total borrowed variables are flexibly specified as indicators for the borrower being in the 1<sup>st</sup> through 10<sup>th</sup> decile of the distribution of the variable (one indicator is excluded in each resulting group of 10 indicators, so there so there are 18 additional variables in each regression.) We cannot reject the hypothesis that fingerprinting has no effect on eventual repayment (columns 4-6) once we control for agricultural profits and original loan size. Coefficient estimates that were previously statistically significant (in Online Appendix Table 4) are now uniformly smaller in magnitude and not statistically significantly different from zero. Indeed, the previously significant coefficients on the fingerprint * quintile 1 interaction across the columns

> 25 We limit ourselves to the 520-observation sample because of the need to control for profits, which was only observed among those in the August 2008 survey. These results should therefore be compared with Online Appendix Table 4, which is also for the 520-observation sample.

25
Policy Research Working Paper 6249

# **Abstract**

Jordan’s economic growth in the past decade has translated into a significant rise in household consumption and a decline in poverty and inequality indicators. Yet, the sentiment of the overall population seems to point to worsening disparities. Using official household expenditure surveys for 2002, 2008, and 2010, this paper analyzes the patterns and determinants of household welfare growth and examines the extent to which economic growth has been inclusive of the more vulnerable groups. Using counterfactual decompositions, the paper dwells first on the dynamics observed behind the drop in poverty and inequality. It then carries out regression analysis using re-centered influence functions to examine the economic determinants of household welfare growth throughout the decade. The paper finds that welfare growth as opposed to welfare distribution was the main driver behind poverty reduction, and that the drop in inequality was primarily driven by a regional catching-up effect. In addition, the analysis identifies rent, access to human capital services, and more importantly employment in the services sector and the public sector as the major determinants of welfare growth in Jordan. Public hiring in particular was used extensively as a tool for poverty alleviation, especially for residents outside the capital.

This paper is a product of the Poverty Reduction and Economic Management Department, Middle East and North Africa 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 wmansour@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
1997; Ravallion and Chen, 2007; de Janvry and Sadoulet, 1996). The impact on non‐service sectors like agriculture and manufacturing which have traditionally been the foci of pro‐poor economic growth strategies, are thus at risk of being implicitly understated by the glamour of the services sector. There is also the Dutch disease problem, with the rapidly expanding export‐ oriented services sector driving up the exchange rate, and making other industries – such as agriculture – less competitive on the international market.

# **3. Theoretical Foundations**

Bhagwati et al (2004) identifies an important feature of the current services trade phenomenon that makes it qualitatively different from the goods trade – the fact that the services currently being traded were previously nontradable. It is only after technological innovations that nontradables have become tradable, with the evolution of nontradable services to tradable services being theoretically linked to the fragmentation<sup>4</sup> of production. Services like back office operations and accounting were previously integrated components of production. However, due to technological advances, the services can now be provided by another producer and used as an intermediate input in production. Fragmentation of production can thus be considered a necessary condition to the tradability of a service.

Fragmentation in a classic Heckscher‐Ohlin (H‐O) model is a useful starting point to understand some of the basic mechanisms by which vertical specialization has led to the trade in services. It is known from Deardorff (1994) that for an integrated world economy (IWE), factor price equalization (FPE) will occur if the world’s factor endowment lens<sup>5</sup> is completely inside the factor use lens<sup>6</sup> . So, if initially the distribution of endowments was such that the factor endowment lens had points outside the factor use lens, then there is no guarantee that factor prices would be the same across the IWE. In the two‐region, two‐factor, and two‐good H‐O model used in Deardorff (2001a), fragmentation is shown to expand the set of ways that factors can be used – and increase the possibility of FPE since there would be fewer endowment points that would be outside the factor use lens.

The intuition here is that different countries have varying factor abundances, where factor prices in each country reflect their relative abundances and how the factors are used for

> 4 This is synonymous with the term vertical specialization, which describes the breaking of a single production process into separable production processes that can occur in distinct stages. 5 This is the set of vectors that is composed of some or all of the factor endowment vectors.

> 6 This is the set of vectors defined by the usage of the factors.

6