rafmacalaba/datause-encoder-data huggingface dataset:
portability of social security entitlements for migrants residing in the partner country. The total number of bilateral social security agreements has significantly increased worldwide: in our whole database, the total number of bilateral social security agreements has grown from 369 in 1980 (counting only one agreement by pair of countries) to 710 in 2010. In 1980, 36 of total bilateral social security agreements signed worldwide included at least an African country. In 2010, 275 of them have been concluded with an African country (whose 111 have been signed between two African countries). The access of migrants to social protection in the host country and the portability of social security entitlements provided by these agreements may promote bilateral migratory flows and influence the migrants’ willingness to return home (thereby affecting the stock of migrants).

Third, Borjas (1999) showed that the importance of welfare benefits in the destination country significantly influenced location decisions made by migrants. Because of the weakness of data on public expenditures in Africa, we used as a third instrument the difference in life expectancy between country L and country j, LLLLLLLLii, considering that it can approximate 12 the “welfare magnet effect” evidenced by Borjas (1999).

Another econometric difficulty relates to the treatment of zero trade flows which are undefined when converted into logarithms. Given the large prevalence of such observations in our data set, we use the Poisson estimator to take into account the information provided by the zero trade flows. The Poisson Pseudo Maximum Likelihood estimator was identified by Santos Silva and Tenreyro (2006) as an efficient way to deal with the zero trade flows in gravity models. Results of Poisson estimates are presented as robustness checks.

# 3.3. Variables and data

The data on migrant populations, our variable of interest, have been obtained from the newly released global bilateral migration data set of the World Bank. This database is described in Özden et al. (2011) and is the most comprehensive database on bilateral migration available at present. In this database, the World Bank relies on the foreign-born condition to define an international migrant. Bilateral exports data were drawn from the Direction of Trade Statistics (DOTS) of the International Monetary Fund.

As control variables we include traditional variables of distance and cultural proximity coming from the CEPII distance database. In addition, we add a dummy equal to one if there

> 12 Several studies suggest however that this welfare magnet effect might not be the principal determinant of immigrants’ location choices (see for instance Zavodny, 1999 or Kaushal, 2005)

10
# Analyses

52. The analysis proceeded through three stages for each of the two outcomes: a) specification of a model with **iio** predictors, which yields baseline empirical evidence about the amount of variation at each level; b) specification of a model which identifies the relevant covari6tes; c) specification of models for the effects of each of the key predictors, controlling for the relevant covariates.

53. The analysis employed a hierarchical linear model as described by Raudenbush & Bryk, (1986) using the computer progfam of Bryk, Raudenbush, Congdon, and Seltzer (1988). Such models have also been labelled "multilevel models" (Aitkin & Longford, 1986; Goldstein, 1987). Lockheed and Longford (1991) were among the firsi to apply these tchniques in studies of Third World countries, and their advantages in this context are also described in detail by Riddell (1989)3. The method enables separate specification of predictors measured at the student and the classroom level. Within-classroom variability is predicted by student-level variables; between-classroom variability is predicted by schoollevel characteristics4.

30ther recent applications of thew ,nethods in research on developing nations are proided by Lockheed and Bruns (1990) Lockheed and Zhao (1991), Raudenbush, Kidchanapanish, and Kang (1991), Raudenbush and Bhumirat (in press), and Riddell and Nyagura (1991). The chief advantages of these approaches is that the analyst is able to take into account the effects of students' shared membership in classrooms and schools, increasing the validity of inferences about the effects of school and classroom policies, measured at the group level, on processes such as teaching and learning that occur within groups.

4 rhe analysis at both levels is computed simultaneously by means of maximum lik-Iihood. Estimation of residual variation within and between classrooms allows one to monitor the predictive power of the model at each level. The method is well-suited to studies of classroom effects because covariates measured at both levels can be controlled. This methodology overcomes the characteristic flaws of standard multiple regression methods in studies of school and classroom effects (see Raudenbush and Bryk's 11988] rev .w). Such flaws include misestimated standard errors, aggregation bias, and erroneous assessments of variance explained.

22
and Central Europe and the Former Soviet Union in 2002, 2005, and late 2008 or early 2009.<sup>13</sup> The second is the Financial Crisis Surveys (FCS), which were conducted in six countries in the middle of 2009.

The surveys provide complementary information. BEEPS provide information on perceived financial constraints over time for most countries in the region. Although the last round of surveys was conducted relatively early in the crisis, we can use BEEPS data to track responses to questions about financial constraints over time for a wide set of countries. As discussed below, because managers‘ perceptions are likely to be forward looking, the responses received at the onset of the crisis should reflect managers‘ initial views about the likely severity of the crisis. In contrast, although the FCS was only conducted in six countries, it provides concrete information on the effect of the crisis as it was unfolding.

# **A. Business Environment and Enterprise Performance Surveys**

BEEPS covers a broad range of issues about the business environment, including access to and the use of financial services. Because one goal was to provide information on a panel of firms over time, considerable effort was made to collect accurate, detailed, and comparable information across survey waves. Despite these intentions, new questions were added to later rounds and some questions were modified in terms of wording or response options.<sup>14</sup> Our study of financial constraints requires an indicator that is comparable over the three rounds. The best candidate is a broad measure of managers‘ views about access to financing: ―Is access to finance, which includes availability and cost, interest rates, fees and collateral requirements, No Obstacle, a Minor obstacle, a Moderate Obstacle, a Major Obstacle, or a Very Severe Obstacle to the current operations of this establishment?‖ This question provides a comprehensive measure of managers‘ views about financial constraints.

> 13 The first round of the BEEPS was conducted in 1999 but the coverage of firms and format of questions was not sufficiently similar to later rounds to include that data in the regression analysis. For purposes of this analysis, we refer to the 2002 survey as being the first round.

> 14 These changes are described in detail in World Bank (2009).

11
**<u>Table 6.  Fuel subsidy per fuel refined product, 2006</u>**

||**Gasoline**|**Kerosene**|**Diesel**|**Total**|
|---|---|---|---|---|
|Economic Price (Rp/liter)|4,950|5,490|5,200||
|Price sales (Rp/liter)|4,500|2,000|4,300||
|Value added tax (Rp.) -10%|391|182|374||
|PBBKB (Rp) – 5%|196||187||
|Net sale price (Rp)|3,913|1,818|3,739||
|Volume (million K liter)|17|10|11|38|
|as percent of total volume (%)|45|26|29|100|
|**Fuel Subsidy per liter**|1,037|3,672|1,461||
|as percent of net sale price (%)|27|202|39||
|**Fuel subsidy**(Rp trillion)|17.6|36.3|16|70.0|
|as percent oftotal fuelsubsidy (%)|25|52|23|100|
|as percent ofGDP(%)|0.5|1.0|0.5|2.0|

_Source: World Bank calculations from presentation by the Ministry of Energy and Mineral Resources/Directorate General Oil and Gas._ International increases in oil prices raise the cost of oil imports as well as the opportunity cost of exports. Fuel subsidies that maintain oil prices below international levels are thus impacted by any fluctuations in international oil prices. If international prices are low enough a liberalization of the fuel market could be executed without an immediate price shock. These international “break even” prices, however, should also be adjusted by taxes and the alpha factor. Thus in January 2007, the international price was only 5 percent higher than the break even price of ‘premium’ low-octane gasoline, 150 percent higher than the kerosene break even price, and 22 percent higher <u>than the automotive diesel break even price. Twelve</u> months later these margins were far greater, making price liberalization far more difficult.

<!-- Start of picture text --> Figure 13. Gasoline prices across Asia and major economies<br>US$ per litre, early June 2008<br>$3.00 Automatic/market<br>Administered<br>$2.50<br>$2.00<br>$1.50<br>$1.00<br>$0.50<br>$0.00<br>VenezuelaIndonesia-MayMalaysia-MayIndonesia-JuneMalaysia-JuneChina U.S.AIndia-MayThailandPhilippinesIndia-JuneJapanSingaporeSouth KoreaHong KongGermanyTurkey<br><!-- End of picture text --> _Source: World Bank calculations based on various national sources and CEIC._ Fuel subsidies tend to be highly regressive in a nation like Indonesia, as the box below describes. There are many additional reasons that make fuel subsidies a far from ideal social safety net:

- 1) Subsidies are grossly inefficient in targeting the poor and thus inefficiently achieve their claimed role of a social safety net (see below on incidence of the Indonesian fuel subsidy).

- 2) Subsidies undermine macroeconomic stability given the pro-cyclicality of international oil price fluctuations. Expenditures on subsidies increase when world oil prices increase, can also be

15
universal service/access and prices, dispute resolution, enforcement of the law, investigation and inspection, fair competition and equality of treatment and sanctions

# _Guidelines for Interconnection_

The ITU/EU study proposes a number of guidelines for interconnection that are intended to facilitate the establishment of a transparent, fair and accessible regulatory environment to prepare the West African countries for opening to full competition. The study also includes a suggested timeline for implementation in view of the ultimate objective of opening of the market in 2007.

The guidelines on interconnection are divided in four categories:

- Guidelines on aspects relating to infrastructure access

- Guidelines on aspects relating to competition

- Guidelines on aspects that are specific to operators with significant market power (SMP)

- Guidelines on aspects specific to the settlements of disputes

The following recommendations on the existing regulatory framework for interconnection were provided by the study: <u>Recommendation 1: Equally important tools, such as carrier selection, number</u> portability, co-location and local loop unbundling, should be included in legislation, interconnection regulations, or orders and supplemented by necessary regulatory decisions.

<u>Recommendation 2: A definition of relevant markets is needed, and a definition of</u> dominant/SMP operators based on international best practice.

<u>Recommendation 3: The obligations of dominant/SMP operators should be listed in</u> detail, and rules and conditions promulgated for their implementation.

<u>Recommendation 4: Dominant/SMP operators should be obliged to issue an interconnect</u> reference offer every year, implement accounting separation, and undergo an annual audit of accounts, in addition to orienting their tariffs towards costs.

<u>Recommendation 5: It is recommended that a time limit should be established for settling</u> disputes relating to interconnection, allowing a margin for the event that the allotted time proves to be inadequate. The referral procedure should be specified in a separate decree.

19
O.A.M.D.G.

under the Drug Act.<sup>19</sup> _Vn_ is a matrix of violence variables including guerrilla or paramilitary presence (dummy), guerrilla attacks and homicides per 100,000 inhabitants. As suggested by our model, we also include a quadratic term of both the guerrilla attack rate and the homicide rate. We test against linearity with a Wald-test.

_v_ is a random village-level factor; and _u_ is an individual level error term, with 2 2 _E_  _uin X_   0 , _Var_  _uin_<sup>_X_</sup>    _u_ , _E_  _vn X_   0 , _Var_  _vn_<sup>_X_</sup>    _v_ and We allow for this latter correlation of household error terms by clustering. Note that the capture rate is measured at the departmental level. We can assume that individual errors, although correlated at the municipal level, are not correlated at the departmental level beyond municipalities. Under this assumption the standard errors clustered at the municipal level only are still valid. We test the sensitivity of our results with different approaches, including: (i) two definitions of income, income (1): salary + asset income, and income (2): salary only; and (ii) two samples: one including every household that reports some kind of income, i.e. households with asset income only, salary only, or both; and one sample including only households that report a salary, i.e. households with a salary only or a salary + asset income. This allows a better comparison of different income measures.

Results-Table 2 shows the results. OLS allows us to test for sample selection issues and we note that the IMR is insignificant.

> 19 See Martínez and Medina (2003) and Martínez, Medina and Steiner (2001).
These values are less realistic based on evidence from other empirical studies (see Kilian, 2020, for a survey). However, I pick these values to demonstrate how the results vary as the oil supply elasticity restriction becomes less binding.

Figure 17 in the Appendix VII.1 presents the impulse responses of the global GDP factor and the real price of oil to U.S. oil supply and U.S. energy efficiency shocks with different upper bounds on the short-run price elasticity of oil supply. The results indicate that as we relax the elasticity constraint, the impact of a U.S. oil supply shock on the real price of oil and the global GDP factor becomes larger, while the impact of a U.S. energy efficiency shock on the same variables decreases. When the upper bound is 0.14, the effect on the global GDP factor of U.S. oil supply and U.S. energy efficiency shocks is almost identical after four quarters. However, the response at impact and during the first two quarters is always larger when triggered by a U.S. energy efficiency shock.

**_Fossil Fuel Data._** Next, I also check the robustness of the empirical results by using fossil fuel consumption data to identify U.S. energy efficiency shocks. Note that the historical decomposition results presented in Section IV.3 are obtained based on an identification of the U.S. energy efficiency shock using U.S. oil consumption data. However, it can be argued, for example, that a positive shock that satisfies the restrictions in Table 1, column 5, does not capture U.S. energy efficiency shocks because the decrease in U.S. oil consumption might be accompanied by an increasing the consumption of other fossil fuels such as coal and natural gas. Examples of such shocks include the increase in coal mining in the United States after the 1970s oil crisis and similarly a surge in natural gas production following the application of hydraulic fracturing and horizontal drilling to the development of shale gas in the 2000s. Thus, I use the following identification as a robustness test to identify U.S. energy efficiency shocks

where the reduced-form residuals, _ut_ , are obtained using data on U.S. fossil fuel consumption instead of U.S. oil consumption.<sup>31</sup> The sign restrictions imposed on the structural impact multiplier matrix, **B0** , to map _ut_ to the structural shocks, _wt_ , remain unchanged.

The results in Figure 18 indicate that the overall findings for the period 2010–2019 are similar to those obtained with U.S. oil consumption data (if we compare the red and orange dashed lines in the Figure 18). The historical counterfactual shows that in the absence of negative U.S. energy efficiency shocks, global GDP would have been higher during the periods that overlap with the first and the second shale oil booms (2012–2014 and 2017–2019, respectively).

> 31Note that the other variables are the same as those used in Table 1.

23
2

# I. **INTRODUCTION**

In this paper we propose a new approach to measuring efficiency, and illustrate it with four applications in the education and health sectors. The paper is motivated by three interrelated ideas. The first is that inefficiency is commonplace, especially in the education and health sectors, but is not ubiquitous—some providers, some local governments, and some countries, are more efficient than others. The second idea is that having data comparing actual performance to „best practice‟ could be useful in exercises aimed at improving provider performance. These might involve users holding providers accountable directly through, for example, voucher schemes. Or they might involve citizens holding politicians accountable for service delivery inefficiencies through the political process, and policymakers then holding service providers accountable through, for example, payment mechanisms that reward good performance or „naming-and-shaming‟ exercises where poor performance is publicized. The third idea behind the paper is that an observation that efforts to date to measure inefficiency and use it in benchmarking exercises have not been altogether satisfactory. Some efforts focus simply on outputs or outcomes without factoring in the expenditures involved (there has been much discussion, for example, about the cross-country variation in education test scores; but it may be the case that the high achievers simply spend more), while studies that _have_ sought to measure efficiency have not apparently had much impact among policymakers (cf. e.g. Burgess 2006; Hollingsworth and Street 2006); we feel this lack of impact derives from skepticism over the methods.

The method we propose and illustrate in this paper blends themes from the two efficiency measurement methodologies used to date, namely Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA).<sup>1</sup> DEA usually focuses on estimating technical inefficiency and constructs an isoquant frontier made up of a set of piecewise linear segments joining a few data points in the input space. The frontier envelopes the data and permits the comparison of a real-life unit to a hypothetical comparator on the piecewise linear segment of the isoquant with the same input proportions. SFA, on the other hand, estimates the production or cost frontier

> 1 For recent surveys of DEA and SFA in education and health, see Worthington (2001) and Hollingsworth (2008). Early published applications of SFA in education and health include Deller and Rudnicki (1993) and Wagstaff (1989) respectively. Early published applications of DEA in education and health include Bessent and Bessent (1980), Ray (1991), Sherman (1984), and Huang and Mclaughlin (1989).
# **Impact of Services Liberalization on Industry Productivity, Exports and**

# **Development: Six Empirical Studies in the Transition Countries**

# **David Tarr**<sup>**1**</sup>

# **I. Introduction**

Services now constitute about 70 percent of global GDP.<sup>2</sup> Moreover, foreign direct investment (FDI) flows have shifted toward services, and now constitute almost half of total FDI flows in developing countries.<sup>3</sup> Recognizing their importance and the need to have special rules to treat trade in services, the General Agreement on Trade in Services (GATS) was incorporated into the World Trade Organization (WTO) when it was formed in the mid-1990s. Further, services are now a key part of the regional agreements of both the United States and the European Union.

The theoretical literature linking services liberalization to productivity increases in the broader economy is well developed. While there is an important emerging empirical literature (briefly surveyed below) that shows that services liberalization leads to productivity improvement and growth, there is a need for additional empirical studies to investigate and test this hypothesis, including its relevance for transition countries. For this reason, the World Bank Institute, under a grant from the Government of Austria, commissioned seven studies under the auspices of the Economic Education Research Consortium (headquartered in Kiev, Ukraine) to

> 1 Consultant and Former Lead Economist, the Word Bank.  I thank the Austrian Government for its support for this project through a grant to the World Bank Institute for development of services sector capacity in the Europe and Central Asia region. I thank Jean-Christophe Maur for encouraging this project, Tom Coupe, Natalia Bystrytrska and Irina Sobetskaya of the Economic Education Research Consortium for their excellent coordination of the author reviews, and  Diana Weinhold, Oleksandr Shepotylo, Volodymyr Vakhitov and Michael Beenstock for serving as expert reviewers of the papers in the project at various stages of their development. The views expressed are those of the author and do not necessarily reflect those of the Austrian Government, the World Bank or its Executive Directors.

> 2 Francois and Hoekman (2010, p. 644).

> 3 See World Bank, _Global Development Finance_ , 2004.

2
36 Tsble 4.10 (Con't.)

|Group|1975|1980|1984|1985|
|---|---|---|---|---|
|Technicdans<br>and<br>Skilled Workers|23.8|13.5|23.8|16.0|
|Workers and<br>Apprendces|71.1|81.7|71.3|77.6|
|TOTAL|100.0|100.0|100.0|100.0|

Source: Svejnar (1984) for 1975. Enterprise sample for 1980,1984, and 1985.

Although knowledge of the impoitarice of base wages, supplements, and bonuses in total compensation is indispensable for understanding enterprise performance and formulation of public policy, no systematic information existed or could be easily obtained on this subject. Therefore, we administered a questionnaire to a stratified random sample of workers, technicians, and managers (612 in total) in a 17-firm subsample of our larger (80-firm) sample. Our analysis of earnings composition and determinants is based on information from these interviews.

As can be seen from.columns 1 and 2 in Table 4.11, the ratio of base wage tQ, t6ial compensation decreases rapidly with increasing education and professional standing. As reflected by the employee survey data, the base wage forms 67 percent of a typical laborer's or unskilled worker's total compensation, but only 24 percent of the high level manager's total compensation. In order to provide a better understanding of this phenomenon, we calculated the proportions of total compensation that are comprised of bonuses and wage supplements, as shown in columns 3 and 4 of Table 4.11. The resulting proportions demonstrate that wage supplements, rather than bonuses, are primarily responsible for increasing the gap between base wage and total compensation as the employee's skill and education increase. Wage supplements represent 44.9 percent of the typical high level manager's total compensation but only 6.2 percent of the typical