rafmacalaba/data-use-mentions-extended huggingface dataset:
2013, Ferreras 2013). As for the impact on the destination country, immigration from corruption-ridden countries tends to boost corruption levels (Dimant et al. 2015). This is in contrast with general migration, which is found to have a positive impact on the institutional quality of the destination country, with reductions in overall corruption levels in countries with a high economic freedom (Clark et al. 2015, Bologna Pavlik et al. 2019).

To further investigate the role of corruption both as a pull factor and as a push factor – – of migration decisions, we use a broad array of subjective and objective corruption measures combined with bilateral migration flow data, exploiting both cross-sectional and time dimensions. Having access to a panel dataset on both bilateral migration flows and corruption levels is a contribution of this paper, and it improves on the most closely related studies that exist on this topic. In particular, both Dimant et al. (2013) and Cooray and Schneider (2015) consider net migration rates, without being able to disentangle whether corruption

> 3These channels are not limited to developing countries. For instance, Morano Foadi (2006) studies the role of corruption on migration flows in Italy.

2
d) income level (USD 900 to 2,200). This methodology is based on a World Bank tool called “Find My Friends” that allows to compare development data to identify common characteristics of countries.

> 20 More precisely, we calculate quantiles by Hazen’s rule, i.e. the quantile is given as Ghana’s (inverse) rank (within the respective comparison group) minus 0.5, and then divided by the number of countries in the respective comparison group. Note, accordingly, that the best (worst) performer will not get a value exactly equal to 1 (0). We multiplied variables with a negative effect on growth (government consumption and inflation) with (-1) for the ease of interpretation.

> 21 The shortcomings in Ghana’s financial system are also investigated in Biekbe (2011).

19
that would signal that markets are not competitive, as well as identifying which characteristics may be associated with it.

We then confront heterogeneity in conditional satisfaction head on by means of mixed (random parameter) ordered probit models. These models extend the mixed logit model to ordinal responses and can be seen as a generalization of the latent class techniques used by Clark (2004). The mixed model not only enables us to identify the mean premium associated

> 4Ghana’s 2010 GNI/capita of $US 1,230 is roughly the average for sub-Saharan Africa ($US 1,176). Though reliable representative labor market data are fairly sparse, our estimates of the share of selfemployment is broadly similar to that for sub-Saharan Africa.

> 5The ILO (2002) estimates that informal sector self-employment alone accounts for 53% of all nonagricultural employment in Sub-Saharan Africa and about a third of all non-agricultural employment in North Africa.

4
working papers and<br>multilateral organization reports (IMF, World Bank, UCLG, UN, ...)|
|Existing<br>Databases|OECD Tax Autonomy, Regional Authority Index, Local Public Finance<br>Datasets (when available); IMF Government Finance Statistics Manuals<br>(Institutional Structure of Government)|

# **Coding Procedures**

Using the following matrix (Table 12), the discretionary power of each layer of government is coded for each identified tax and revenue source, and across four types of decisions: instrument, base, rates and administration.

- a. _Instrument_ refers to the ability of each government tier to establish or alter an existing instrument.

- b. _Base_ indicates which layer of government is involved in defining the taxable base or granting relief. While the tax bases are often defined single-handedly by central

37
Figure 3 shows the distribution of the percentage of the contract period elapsed within the estimation sample. It includes 3,976 projects, of which 167 were canceled. The vast majority of projects had not passed half of their contract periods. One reason for this finding is that PPPs are a relatively new phenomenon compared with the median contract period of a PPP in the sample, which is 25 years. Another is that crucial information on some of the older projects in the PPI database is missing, such as the contract period and the level of contracting government, forcing us to drop them from the sample used for the econometric estimation.

**Figure 3 Distribution of percentage of contract period elapsed**

<!-- Start of picture text --> 700<br>600<br>500<br>400<br>300<br>200<br>100<br>0<br>0 10 20 30 40 50 60 70 80 90 100<br>Percent of contract period elapsed<br>Number of projects<br><!-- End of picture text --> _Source_ : PPI database.

# **_4.3 Estimation Results_**

Nonparametric estimates using all PPP projects in low- and middle-income countries show that PPP projects are more likely to fail during early in their contract periods and that the risks accumulated during their contract periods are not trivial. The smoothed hazard rate estimate using Gaussian kernel and optimal bandwidth indicates a unimodal hazard profile for a PPP project (figure 4). The risk of early termination for a project increases rapidly until about 20 percent of the project’s contract period elapses. It plateaus at this level before declining slightly until it reaches 50 percent. During the second half of the contract period, the risk of early termination decreases until the project approaches the end of the contract period, except for a small increase at about the 80 percent mark.

The cumulative hazard curve shows that the accumulated probability of early termination increases steadily
BEC classification to identify a sample of consumption goods for use in a robustness check.

be imperfect, but quite reasonable.

> 16We exclude imports from Canada and Mexico in these calculations so the U.S. data we use reflect the air-vs-sea choice that is available to shippers on PR routes. In this we follow Hummels and Schaur (2013) who use air and sea shipments to measure the value of time in the movement of U.S. import shipments. All U.S. export and import data files were taken from (U.S. Census Bureau, 2018). All dollar values are deflated by the U.S. consumer price index and expressed in 2019 dollars.

10
Figure 7 highlights that significant gains in productivity are achievable if full relaxation of business environment constraints were possible. The gains in productivity are calculated based on existing resource inputs and technology. We calculate that these potential levels of output could alternatively be achieved in 15 to 20 years if the economy grew at eight percent per annum from its current levels of output and value added. Our productivity frontier analysis therefore implies, under the assumption of a smooth transition in policies and constant inputs and technology, that policies which incrementally relax business environment constraints over a period of 15 to 20 years could be expected to induce eight percent growth in manufacturing output and value added per annum (Table 6).

# **VI. Firm-level TFP Analysis**

# **Data sources**

A 2011 World Bank Enterprise Survey (WBES), covering data from fiscal year 2010, was conducted as a follow-up to the original 2004 WBES (which covered fiscal year 2003). For comparability across both years, and to allow calculation of TFP based on reliable capital asset estimates, we restrict our focus here to manufacturing establishments (the 2003 sample consisted exclusively of manufacturing establishments). The 2010 manufacturing subset of the survey is comprised of 330 establishments.

Summary statistics of the 2010 manufacturing data, and the comparable 2003 data, are presented in the second through fourth columns of Table 3. The second column presents means based on all available manufacturing establishments included in the 2010 sample. There are stark differences between these 330 establishments and the 408 establishments sampled in 2003:<sup>15</sup> only 3 percent of the 2010 establishments have more than 10% foreign ownership, while 19 percent of the 2003 establishments had this level of foreign ownership; conversely, less than 22 percent of 2010 establishments export while 68 percent of 2003 establishments exported. These differences are no doubt related to underlying differences in establishment characteristics: while the 2003 sample contained mainly larger firms with only 6 percent of establishments being micro-sized (10 employees or less), 41 percent
Fidrmuc 2015), literacy rates and linguistic diversity (Melitz 2008), population and population dispersion (Chung and Wall 2005), and a common currency (Head et al. 2010), and policies that might affect demand or production costs, such as labor compliance.

We first follow the commonly used log-linearized form (LLF) to estimate equation (1). However, we acknowledge the potential biases of zero trade flows occurrences and the heteroskedasticity often found in trade data raised by Head and Meyer (2014) and Yotov et al. (2016). Zero trade observations do not occur randomly and when used in a log-linear model they are automatically dropped from the estimation since the logarithm of zero is undefined. The latter not only renders parts of the data unusable for estimation but bias the estimates of the effects of trade costs and trade policy and is also inconsistent with the LLF of the OLS estimator or other approaches that require a non-linear transformation.<sup>6</sup> Dropping these observations or adding one with the goal to have defined logarithms are not potential solutions as they generate information losses and do not solve the problem of a biased estimation.

To address concerns related to the log linearized estimation, we follow the literature (Santos Silva and Tenreyro, 2006; Yotov et al., 2016) and proceed with a second estimation of (1) using a Pseudo Poisson Maximum Likelihood (PPML) estimator. This approach allows to directly use the levels of the dependent variable (instead of the logarithm), avoiding dropping zero trade flow observations. Further, the PPML is a robust approach to the presence of heteroskedasticity (Burger, Van Oort, and Linders 2009, Silva and Tenreyro 2011, Martínez-Zarzoso 2013). Thus, we us it as our main empirical strategy for the gravity analysis. We also include country-specific fixed effects to address potential trade multilateral resistance –the barriers to trade each country faces with all its trading partners– and country-pair fixed effects to control for the endogeneity of trade agreements (
." Journal of Health Economics. 15:333-357.

Lewis, Maureen a., Gerald M. La Forgia, and Margaret B. Sulvetta, 1996. 'Measuring Public Hospital Costs: Empirical Evidence from the Dominican Republic," Social Science zmd Medicine, 43(2):221-234.

Lopez, Alan D., 1993. 'Causes of Death in Industrial and Developing Counties: Estimates for 1985-1990," in Disease Control Priorities in Dleveloing Countries, Jamison et al eds.

Makinen, Marty and Laura Raney, 1994. "Role and Desirability of User Charges for Health Services,' Draft Working Paper. Bethesda, MD.: Abt Associates.

Manniing, Willard G., Joseph P. Newhouse, Naihua Duan, Emmett B3. Keeler, Arleen Leibowitz, and M. Susan Marquis, 1987. "Health Insurance and tie Demand for Medical Care: Evidence from a Randomized Experiment," _Arian_ EcnomicRvie, 77(3):251-77.

Martines, Jose, Margaret Phillips, and Richard g. Feqchem, 1993. "Diarrheal Diseases," in Disease Contro Prioris in Developing Countries, Jamison et al eds.

Menken, Jane, and James Phillips, 1990. "Population Change in a Rural Area of Bangladesh, 1967-87," 1a Anrals of the American Academy, 510:87-101.

53
compares three computational methods for obtaining the return on a portfolio of securities over an interval of time:

- arithmetic: the mean daily return is obtained by averaging across both firms and days-this is then compounded to give the portfolio return over a longer period;

- rebalanced: the return on a portfolio is rebalanced at the end of each period to maintain equal investments;

- buy-and-hold: individual security returns over the required time period are calculated from daily returns and then averaged over securities to give the portfolio return.

Roll finds that the method used to calculate mean returns has a significant effect on the estimated return, such that the apparent premium to holding a portfolio made up of smaller rather than larger issues is approximately halved when the buy-and-hold approach is used. He argues that this method is the most plausible as it mimics the behaviour of actual investors, as their transaction costs prevent regular rebalancing of portfolios. The buy-and-hold approach is the preferred method used in academic work on the estimation of beta values, such as Handa et al. (1989).' In making international comparisons, it is important to ensure that returns data is calculated on the same basis, which should preferably be the buy-and-hold method. This may require new market indices to be calculated, as published indices tend to be rebalanced and the frequency of adjustment is likely to vary across countries.

> 8 Handa, Kothari and Wasley (1989), 'The Relation Between the Return Interval and Betas', _Journal of Financial Economics,_ 23, 79-100.

35
training extends from the standard two days (for U.S. high-inference tools) to four days, which allows for additional time to practice coding additional videos, and conduct a field visit where participants participate in live classroom observations.

Before observers can code using _Teach_ , they are required to pass a certification exam that involves scoring three videos within 1-point of the master codes at least 80% of the time. Analyses of the training data from Mozambique, Pakistan, the Philippines, and Uruguay indicate that of 145 participants, almost 90% (130), passed the exam. The lowest passage rate was in Mozambique, with 34 of 46 participants passing. The highest passage rate was in Uruguay, with 21 of 21 participants passing. In all four countries, local observers conducted the observations. These observers had a comparable level of education to the average citizen in their country and had no previous experience conducting classroom observations.

After the piloting, the tool underwent additional changes based on the feedback from training participants and data from the certification exam. For example, the critical thinking element was difficult for observers to understand and code consistently. To address this shortfall, the _Teach_ team created a comprehensive table with examples for each subject and quality range. This was designed to aid the observers in processing and interpreting the information from the observation and manual.

# 4. Coherence and Correlation

# 4.1 Methods

## 4.1.1. Participants and Setting

We use data from the SABER Service Delivery (SABER SD) survey — which collects information with the goal of standardizing measures of student learning, teacher and school management quality, infrastructure and learning material, and student preparedness. The SABER SD survey grew out of a concern for poor learning outcomes, as evidenced by student tests and service delivery shortfalls. The survey builds upon the SABER (Systems Approach for Better Education Results) and SDI (Service Delivery Indicators) surveys (Bold et al., 2017).

For this study, we use a representative sample of
The HEIDE data set may lead to different conclusions for two reasons. First, conditions in the transition countries may have changed from the time period referenced by the Poverty Assessments and that covered by the HEIDE data base. Second, as described in the methodological section, the HEIDE data base uses an equivalent adult approach (which was not usually followed in Poverty Assessments), a relative poverty line, and relied on self-reporting for the value of food produced by the household for its own consumption. In most of the World Bank's poverty assessments for the FSU, the value of food produced on private plots was imputed, usually based on the purchase prices reported by all the households in the sample. Imputing the value of food this way tends to lead to a higher consumption aggregate than asking respondents to assess the market value of their food production.

In Estonia, there is little difference between the depth of poverty in Talinn, the capital, in other cities, or in rural areas as measured by the poverty gap. In Kyrgyz Republic, the average poverty gap seems to be most affected by the higher poverty gap in other cities, since there is little difference between the poverty rate in the capital and the countryside. In Russia, the poverty gap is highest in rural areas and noticeably lower in the capital.

# **Family Composition**

It is a truism of poverty studies that family composition is one of the most significant correlates of poverty, since the number of earners and dependents has a critical impact on the family's consumption needs and ability to fulfill those needs. In the FSU, however, family composition does not correlate as strongly with poverty as it does in 46
16 Bulgaria and Romania. The former stands out because of a weaker performance, whereas the latter due to a stronger performance throughout the whole period. They experienced slow down in 1998-99 (Turkey also a contraction in 2000) and subsequently impressive expansion (Figure 5). The increase in Turkey’s share by 10 percent in 2003 over 2002 was larger than for the EU-8 and Romania—both 9 percent.

Similarities between the aggregate performance of the EU-8, which in terms of population roughly equals Turkey’s, and Turkey go beyond the time profile over 1996-2003. The factors accountable for the improvement in their export performance in EU markets have been also similar. One may distinguish three factors accountable for change in exports—import demand, competitiveness and diversification. When a country merely maintains its share in imports, the increase in exports is to the growth in import demand. When it increases more than import demand, then these extra exports can be attributable to increased competitiveness. When the increase comes from new exports, it is due to the diversification effect. Table 8 presents the results of calculations of factors of growth in EU-15 oriented exports of EU Eastern Enlargement countries in 2000-04 using four-digit SITC data for EU imports. For each four-digit SITC sector, the shares of regional suppliers in EU imports are calculated for 2000 and 2004. The growth in import demand was accountable for 52 percent of the increase in Turkish exports between 2000 and 2004, the growth in competitiveness for 48 percent of the increase, and the growth in diversification for 1 percent of the increase in exports. Decomposed factors accountable for the expansion of Turkey’s EU-15-oriented exports are very similar to those explaining the growth in exports from the EU-8 economies. Except for Croatia, other countries have capitalized not only on the EU-15 demand for exports due to income growth but also succeeded in exploiting costeffective advantages.

**Table 8:** _Sources of growth in EU-oriented exports in regional perspective in 2000-04_

||Ex|ports ($ m<br>|illion
usually pay a funding premium on top of the sovereign rate.<sup>2</sup> If the efficiencies in project execution are systematically overestimated or the contingent liabilities from risk and uncertainty are underestimated, the government may be better off executing investments through conventional contracting of the private sector or even SOEs.

The rising popularity of PPPs means that careful management of the fiscal risks that they pose has become exceedingly important. However, opacity of financial records, confidentiality of most PPP contracts, and the prevalence of cash rather than accrual accounting systems in emerging markets and developing economies hide the fiscal risks for government finances until the contingent liability materializes.

This paper tries to assess the fiscal risks to governments from early termination of infrastructure PPPs, using the value-at-risk methodology. It gauges the expected loss from a PPP project using the probability of early termination, the exposure of the government in the event of early termination, and the loss given early termination. Using data from the World Bank’s Private Participation in Infrastructure (PPI) database, _World Development Indicators_ , the Polity IV Project, and Laeven and Valencia (2020), the study identifies systematic contractual, institutional, and macroeconomic factors that can help predict the probability that a PPP project will be terminated early using a flexible parametric hazard regression.

The analysis finds that, in the developing world, PPPs have a lower probability of early termination when they are (a) contracted by subnational entities; (b) backed by direct support from the government (including capital grants, revenue subsidies, and in-kind transfers); and (c) originated in countries with greater constraints on executive power. Large physical investments and macro-financial shocks increase the likelihood of early terminations.

We estimate the fiscal risks from each country’s active portfolio of PPP projects using a value-atrisk approach under three scenarios. Each scenario assumes different government losses given early termination. The results show that the 99 percent value at risk from early termination of PPPs can be as high as 0.89 percent of GDP in
distress|X|Blend|
|Guyana||X|||Moderate||IDA|
|Kiribati|||X|X|High|X|IDA|
|Maldives|X||||High||IDA|
|Marshall Islands|X||X|X|High|X|IDA|
|Mauritius|X||||||IBRD|
|Micronesia, Fed Sts.|X||X|X|High|X|IDA|
|Montenegro|X||||||IBRD|
|Nauru||||X||X|IBRD|
|Palau|X|||X||X|IBRD|
|Samoa|X||||High|X|IDA|
|São Tomé and Príncipe||X|X||In distress|X|IDA|
|Seychelles|X|X||X|||IBRD|
|Solomon Islands||X|X||Moderate|X|IDA|
|St. Kitts and Nevis|X|||X|||IBRD|
|St. Lucia|X|||X|||Blend|
|St. Vincent and the<br>Grenadines|X|||X|High||Blend|
|Suriname||X|||||IBRD|
|Timor-Leste||X|X||Moderate|X|Blend|
|Tonga|X|||X|High|X|IDA|
|Tuvalu|||X|X|High|X|IDA|
|Vanuatu|X||||Moderate|X|IDA|

_Sources_ : GFS (database); UN World Tourism Organization; World Bank.

23
August 12, 2019. Available at: <u>https://results.org/blog/investing_in_every_childs_early_years_world_bank_contributions/.</u> 2 For details refer to Appendix 4 in Hasan, Hyson and Chang, 2013.

> 3 A comparison of assets ownership by households in the evaluation sample with that of the rural sub-sample of the SUSENAS (a nationally representative household survey) suggests average rates of asset ownership and education levels are by and large similar between the two.

1
from Muslim countries in the Middle-East and North-Africa. Tables A.1 to A.5 in the Appendix reproduce the content of Table 1 separately for Mexico, India, China, Philippines, and the MENA region. Interestingly, we see that the likelihood of marrying a U.S. native after migration is substantially lower for Chinese (4.2 percent) and Indian (8.1 percent) compared to Mexican (22.5 percent) and Middle-Eastern and North-African (23.8 percent); the likelihood of intermarrying with a U.S. native is also particularly high for women from the Philippines (39.3 percent) compared to women from other countries (less than 20 percent).

The ACS data can be further used to provide descriptive evidence on the evolution of the probability of a change in marital status with the time since migration as a function of the

> 16Notice, as this might appear surprising, that the ACS provides information on the year in which an immigrant moved to the U.S. for the last time; multiple migration spells, which remain unobserved in the data, together with the possibility that the spouse is a second-generation immigrant from the same origin who also migrated in the past, might explain why some individuals appeared to have married a native before migration.

18