rafmacalaba/data-use-mentions-extended huggingface dataset:
9 of health system performance (see e.g. Hakkinen and Joumard 2007). Throughput measures— such as inpatient admissions, and ambulatory care visits—are just that, and need not necessarily capture the ultimate outcome of interest, namely better health. But health indicators such as mortality (or life expectancy) and disability reflect many factors beyond the control of the health sector: deaths from road accidents likely reflect road safety improvements more than health spending, and many deaths are from causes that are still not amenable to medical intervention. Arguably a more compelling approach when assessing the efficiency of a country‟s health spending is to link health spending to deaths from conditions that _are_ amenable to medical care (Nolte and McKee 2008). This is what we do in this study.

Our data come from the OECD‟s Health Data. We have data for 29 countries over the period 1960-2005. Not all countries have data for every year. Health spending is defined as total health spending (i.e. public plus private) measured in 2000 prices in international dollars. Mortality is measured through potential years of life lost (PYLL) among people below the age of 70 who die from nine causes of death that are „amenable‟ to medical care, i.e. causes where timely and effective medical care can result in a death being avoided. We select the conditions from Nolte and McKee (2008) who identify a longer list of conditions but only nine are included in the OECD PYLL database. Deaths among older age groups are excluded by the OECD on the grounds that they are less easily amenable to medical care. We aggregate some of the conditions so we are left with a more manageable six PYLL „outputs‟.<sup>11</sup> Our measure of health sector output—while preferable to a throughput measure and better than all-cause mortality among all age groups—is not without its limitations, of course. It focuses on length of life rather than quality of life and does
, The theory of peasant economy (Irwin, Homewood, IL).

<mark>Firpo, S., Fortin, N.M. and Lemieux, T., 2009. Unconditional quantile regressions.</mark> _<mark>Econometrica</mark>_ <mark>,</mark> _<mark>77</mark>_ <mark>(3), pp.953-973.</mark> <mark>Gilbert, R.A., Sakala, W.D. and Benson, T.D., 2002. Gender Analysis of a Nationwide Cropping System Trial Survey in Malawi.</mark> _<mark>African Studies Quarterly</mark>_ <mark>,</mark> _<mark>6</mark>_ <mark>(1-2), pp.223-243.</mark> <mark>Halvorsen, R. and Palmquist, R., 1980. The interpretation of dummy variables in semilogarithmic equations.</mark> _<mark>American economic review</mark>_ <mark>,</mark> _<mark>70</mark>_ <mark>(3), pp.474-475.</mark> <mark>Kimhi, A., 2006. Plot size and maize productivity in Zambia: is there an inverse relationship?.</mark> _<mark>Agricultural Economics</mark>_ <mark>,</mark> _<mark>35</mark>_ <mark>(1), pp.1-9.</mark> <mark>Kinkingninhoun-Mêdagbé, F.M., Diagne, A., Simtowe, F., Agboh-Noameshie, A.R. and Adégbola, P.Y., 2010. Gender discrimination and its impact on income, productivity, and technical efficiency: evidence from Benin.</mark> _<mark>Agriculture and
port authorities to attract traffic (basically through tariffs), coupled with the difficulty in adjusting inputs (mainly quasi-fixed inputs), which implies that the likely desirable orientation of the distance function is an output-orientation.

Empirically, the paper has shown that the restructuring and the substantial reforms introduced not only changed the conditions for the development of port activities subject to regulation but also led to significant improvements in technological change. Technical efficiency has however not improved in a similar way and has in fact changed little on average. There is however a significant movement of the efficiency within ports over time as a result of reforms.

These results are particularly relevant in practice because a third wave of reforms has just been implemented and many more changes are expected to come from forthcoming European Union guidelines for the liberalization of port activities with potentially strong influence for container traffic. The results provided here however show that island and mainland ports are likely to be influenced differently if the past is considered to be a valid indication of the future reaction of port authorities to reform.

# **References**

Baird, A. (1995) “Privatization of Trust Ports in the United Kingdom: Review and Analysis of the First Sales”, _Transport Policy_ , 2: 135-143.

Baños Pino, J., Coto Millán, P. and Rodríguez Álvarez, A. (1999) “Allocative Efficiency and Over-capitalization: an Application”, _International Journal of Transport Economics_ , XXVI (2): 181-199.

Battese, G.E. and Coelli, T.J. (1995) “A Model for Technical Inefficiency Effects in a Stochastic Frontier Production for Panel Data”, _Empirical Economics_ , 20: 325-33.

Battese, G.E., and Coelli, T.J. (1988) “Prediction of Firm-Level Technical Efficiencies with a Generalized Frontier Production Function and Panel Data”, _Journal of Econometrics_ , 38: 387-399.

Bennathan, E. and Walters, A.A. (1979) _Port Pricing and Investment Policy for Developing Countries_ , Oxford
In order to use these estimates in the context of our static model, we cannot simply use the total costs computed above and compare those to a single year of annual gain. Indeed, the model is calibrated using yearly data (trade flows and GDP are annual) and hence total consumption levels found in our simulated results are comparable to one year of consumption.

One way to compare the cost and benefits of investing in transport infrastructure using such a static model could be to compare the one-time initial cost payment to the present discounted value of the benefits that will be felt from the investment onward. Let Gn be the total annual welfare gain for a country in terms of real consumption, Gn = In − In<sup>′</sup> , and Dn the one-time investment Pn Pn<sup>′</sup> cost. Assuming a constant discount rate r, we could compute the net gain as the difference between the net present value of all gains and the one-time initial cost: However, such an approach would assume that the whole cost of infrastructure is paid in full in the first year and the benefits are felt thereafter. In our model, this would imply setting the L annual lump sum tax for the household to zero (τn = 0) and assuming that investment occurs _before_ solving for the equilibrium. By doing this, however, we would not properly account for the interaction between the investment cost in the household budget constraint and the equilibrium allocation: since countries have different consumption baskets and sectoral distributions, it is important to be able to incorporate the investment cost within the annual equilibrium structure described above.

To take into account the costs of infrastructures in a way consistent with the static model and its annual equilibrium, we use an “annualized” cost which allows us to compare one year of household revenues to one “yearly equivalent” of the investment cost. To do so, we simply assume that the costs are paid through a perpetuity with interest rate r. The equivalent annuity for
T. (1994). Effects of early intervention on intellectual and academic achievement: a follow-up study of children from low-income families. _Child development_ , 65(2):684–698.

- Campbell, F. A., Ramey, C. T., Pungello, E., Sparling, J., and Miller-Johnson, S. (2002). Early childhood education: Young adult outcomes from the abecedarian project. _Applied developmental science_ , 6(1):42–57.

- Carneiro, P., Lken, K. V., and Salvanes, K. G. (2015). A flying start? Maternity leave benefits and long-run outcomes of children. _Journal of Political Economy_ , 123(2):365–412.

- Carneiro, P., Meghir, C., and Parey, M. (2013). Maternal education, home environments, and the development of children and adolescents. _Journal of the European Economic Association_ , 11(suppl ~~1~~ ):123–160.

- Cascio, E. U. (2009). Maternal labor supply and the introduction of kindergartens into american public schools. _Journal of Human resources_ , 44(1):140–170.

- Cascio, E. U. (2021). Does universal preschool hit the target? program access and preschool impacts. _Journal of Human Resources_ , pages 0220–10728R1.

- Chiappori, P.-A., Dias, M. C., and Meghir, C. (2018). The marriage market, labor supply, and education choice. _Journal of Political Economy_ , 126(S1):S26–S72.

- Chzhen, Y., Rees, G., and Gromada, A. (2019). Are the world’s richest countries family friendly? Policy in the OECD and EU. _UNICEF Office of Research_ .

- Ciliberto, F. and Tamer, E. (2009). Market structure and multiple
labor and agricultural value-added. This can give rise to misleading inferences, when one aggregates the household results up to the national level.

An example of this problem arises in two recent studies of the poverty impact of China’s WTO accession. The first is a global CGE analysis in which final demand in China is modeled via a single representative consumer (Ianchovichina and Martin, 2003). They find that China as a whole gains from accession. However, those authors are unable to speak to the poverty issue. Towards this end, a second study (Chen and Ravallion, 2003) takes the price changes from the global CGE study and applies them at the individual household level to elicit the distributional consequences of accession using full detail in the household survey. Thus the authors are able to identify which types of households in which provinces and with which demographics lose and which gain. This is extremely useful information.

However, when the individual household impacts are aggregated up to the national level, China is found to lose, not gain, from WTO accession, thereby contradicting the original macro results from which the household impacts are driven. It is easy to see why this might be the case. Agriculture is hurt most by WTO accession and if this portion of national income is overstated in the survey, then it will take on disproportionate importance in the estimated national impacts – thereby giving the misleading impression of an overall loss. Such contradictions are pervasive in the so-called micromacro synthesis literature, and this highlights the need to reconcile the underlying data bases before undertaking serious policy analysis (Ivanic, 2004).

**_Tax Revenue and Transfer Payments:_** Trade taxes are an important part of total revenue in many developing countries and so the fiscal implications of their reduction or elimination under various trade reform scenarios needs to be given serious consideration (Harrison, Rutherford, and Tarr, 2000). Depending on the choice of tax replacement instrument, the poor may be adversely affected. For example, value-added taxes are a common alternative
|1.32|39.2|60.8|100 %|
|3,000|10,000|82.7|22.6|1.46|35.9|64.1|100 %|

Source: authors' calculation based on data in table 5.

a/ This column corresponds to the right-hand-side of equation (3) and is the product of country B's advantage over A in coverage and in the pupil-teache **r** atio. Note that the data are close to the figures in column 3 of table 2.5, which correspond to the left-hand-side of equation (3).

_Comparing resource availability and deployment in 1993 and 1975._ Do the same patterns in resource availability and deployment characterize richer and poorer countries in an early period? To find out, we compared the same pairs of countries presented above, using data for 1975. We chose this year because it is sufficiently far back to offer a long-term perspective and because data are still available for a sufficiently large number of countries on the key indicators.

The results pertaining to resource availability appear in figure 11, which also includes the data for 1993 as a reference.31 The pattern in 1975 is comparable to that in the later year in that the resources for primary education are always more plentiful in the richer country in each pair. For all income pairs except the first ($200 and $400), the advantage in 1993 slightly exceeds that in 1975.

> **31** Another way to view the differences between 1995 and 1993 is to compare countries at the same level of per capita GNP in the two years; the results appear in appendix A and confirm the pattems discussed here.
wages and employment using data on manufacturing employees from SAKERNAS, a nationally representative labor force survey in Indonesia. We cannot tell from this labor force survey the characteristics of the employer, but the labor force data enable us to control for individual characteristics and the comparison with the firm-level data highlights the extent to which the patterns for the larger formal manufacturing sector were mirrored in the broader population of manufacturing workers.

> 4 For example, if women are always more likely to be laid off when a firm is forced to downsize, one might also expect them to be more likely to be laid off in times of crisis. Alternatively, it could be the case that women are only discriminated against during times of extreme economic stress, but not in less turbulent times. An interesting question in this regard is whether women suffer disproportionately during the crisis relative to other times. We address this by examining how differential treatment during the crisis differed from differential treatment during non-crisis times.

4
of households that qualify for the humanitarian MPCA assistance to be eligible for the government’s cash transfer program. While the referral accuracy of the PPMT models are high (low inclusion error), they are also likely to leave out a number of eligible households (high exclusion error). Following Phadera et al. (2022), the crossreferrals are examined under two vulnerability assessment models used by the MPCA program - the legacy Vulnerable Assessment model (Legacy -VA; referred to as VM in Phadera et al. (2022)) and the updated 2019 model called the Socio-Economic Vulnerability Assessment Tool (SEVAT). The analysis shows that 40 percent of the households identified as <mark>extremely vulnerable by the SEVAT model would also be considered as poor by the MoLSA PMT scoring and, thus, would be eligible for the government’s cash transfer program under a scenario where the program expansion is limited to those below the national poverty line of IQD 110,000 per capita consumption per month (a medium-small program). For the same expansion, the referral rate for the Legacy-VA extreme vulnerable group would be about 20 percent. Again, as per the desk review recommendation,</mark> the <mark>PPMT performance is evaluated under two</mark> 5
The two-stage sampling design of the DHS and most other household surveys, however, violates the assumption of independent observations. Households in a given cluster are more likely to be similar to one another in some respects than households in different clusters. The weighted or unweighted mean of variables are not affected by the two-stage design, but the design does increase the variability of these estimates compared with a simple random sampling design. If the sample design is ignored, the variance of estimated means using standard formulas will be too small. In addition, since the error terms in the regression are correlated across observations in the same cluster, without some procedure to correct these standard errors, the efficiency of the coefficients estimated will be affected (Deaton, 1997).

Unless one fully parameterizes the correlation within clusters, the true likelihood function for the clustered sample cannot be written.<sup>11</sup> However, the model can be estimated without parameterization of the within-cluster correlation using appropriate statistical techniques. These will estimate the β vector that maximizes the likelihood function that we would have if we had data on all individuals in the population. The variance estimates are computed as if the sample was drawn again and again using the same clustering scheme and the estimated β vector computed as the maximum of the “pseudo-likelihood”.<sup>12</sup> Another issue of concern for the estimation of the above model is the possible endogeneity of some of the variables chosen as explanatory variables. For example, if household access to water or sanitation is a choice variable, then it may be correlated with the unobservables attributed to the error term. Endogeneity may also be a concern with the use the mother’s BMI as a proxy for household food security. Failure to control for possible endogenous variables could lead to biased estimates. To test for the possibility of endogenous variables, two estimators can be compared, one consistent (and efficient) under the hypothesis that there is no endogeneity, but inconsistent if there is endogeneity, and the
|10,033|
|_R2_|0.082|0.146|0.140|
|* p <|0.05, ** p < 0.01, *** p|< 0.001||

_Notes:_ All regressions control for pre-treatment outcomes, demographic controls (including dummies for age, gender, academic year, and ethnicity), and municipality fixed effects. Robust standard errors are clustered at the school level in parentheses. All figures are rounded to three decimal places. _Source:_ Own survey data, administrative data, school year 2015/2016, own calculations.

40
**<u>Table 1: Share of SP spending as % of GDP by year stratified by 1995 GDP per capita</u>**

|GDP per capita by<br>1995 quintiles|1995|2000|2005|2010|2015|2019|
|---|---|---|---|---|---|---|
|1 (lowest)|1.37|1.68|2.47|3.26|3.52|4.20|
|2|3.49|6.64|5.19|6.36|5.74|6.01|
|3|4.57|4.90|4.84|6.75|6.18|6.83|
|4|9.59|10.00|9.64|10.97|10.24|10.37|
|5|14.16|12.79|13.17|14.92|15.02|14.72|
|Total|8.15|8.35|8.07|8.84|8.48|8.91|

<u>Source: Authors’ calculations from the data set described in Section 3 and the Addendum.</u> 36
**Appendix 3: Data Sources**

Data on reserves accumulation and on imports and exports of goods and services (exclusive of interest payments) were obtained from the International Monetary Fund's balance of payments database for all countries in the sample. Data on net transfers of official and private flows were obtained from the World Bank's Debtor Reporting System database, which reports actual cash flows. Data on ODA debt forgiveness and pure grants was obtained from the OECD's Development Assistance Committee Creditor Reporting System Database. Because the ODA debt forgiveness data were collected recently and are not yet fully consolidated, and some differences remain in the way donor countries report debt forgiveness, the results reported in the paper should be interpreted with some caution.

25
of procedures to register a property from DB database to construct a measure of the ease of doing business in a country.

Our firm-level controls are taken from the WBES and comprise firm productivity (real sales per employee) and a vector of indicator variables for whether a firm exports; is publicly traded; has foreign or state ownership; is of medium or large size; communicates with customers using e-mail or website; and has been in operation for less than five years.

Table 1 displays summary statistics of the main variables of interest. A full list of the variables with definitions is provided in Appendix A. Tables A.1–A.3 in the Online Appendix present additional statistics and correlations between the variables.

# **3. Empirical strategy**

To assess the impact of e-filing implementation at the country level, we employ a difference-indifference (DID) approach in a fixed effects estimation framework. The treatment is the year of e-filing implementation, which varies across countries. Countries that adopted e-filing systems during the sample period are the treated group, and countries that had implemented an e-filing system before 2005 or had not adopted a system by the end of the sample period are the control group. The inclusion in the

> 7 The _Enterprise Surveys_ are also known as the _Business Environment and Enterprise Performance Surveys_ (BEEPS) in the Europe and Central Asia (ECA) region.

6
sector development and growth (World Bank Investment Climate Database). Thus the longer governments wait to address these issues, the greater the economic and financial burden and the greater the barriers to achieving economic growth.

# **IV.   EMERGING ISSUES**

44. A vast body of empirical work on the impact of privatization that has been summarized in detail elsewhere shows that in competitive sectors privatization has improved firm performance (Megginson and Netter 2003 and Kikeri and Nellis 2004 provide recent reviews). Available studies conclude that privatization in these sectors improves performance and
“broad” classification that adds to the “typical” one the columns that pertain to utilities, half of the columns with postal and telecommunication services, and one third of the land transport column. The empirical evidence that we present in this and in the next sections relies on the “typical” definition, and we check the robustness of our main results to the use of the “narrow” definition (the results are shown in the Appendix). Because the TiVA data are not detailed enough (i.e., land transportation is included in a broader “transport and storage” sector), we cannot appropriately implement the “broad” definition.

Once public procurement is defined, we identify a private market that is suitable for comparisons. The sum of the other columns in the ICIO table and the “Household expenditure” column in the final demand section is the most immediate and comparable definition of ‘private procurement’. This choice can nevertheless lead to an overlapping with government procurement to the extent to which public authorities operate outside the “typical” definition of government (i.e., outside the Public Administration, Health, and Education columns). Such an overlap between the public and private markets should work against finding significant differences in trade barriers between the two.

# **4 Descriptive trends**

Before turning to the empirical estimates of the gravity models, we investigate descriptive trends in the data. The objective here is twofold: (i) to identify patterns of expenditures across goods and services in public and private markets as these affect estimated home bias at the country-level; and (ii) to have a first look at trade barriers by looking at import penetration ratios. First, we compute the service expenditure share for each country in the ‘typical’ public and private markets as defined above. Figure 2 reports this share for 1995 and 2015, the first and the last years of our sample. One pattern stands out: government procurement is vastly about services. The average government in
coupled with regulatory independence, effective control of monopoly power, and efficient taxation of digital services, can catalyze private sector investment to lower the cost of access to digital services and increase use of the internet, with positive spillovers to the rest of the economy (Arezki et al. 2021; Rodriguez-Castelan et al. 2021). Public investment can also play a role in supporting the digital transformation for firms by reducing cost barriers and accelerating digitalization, particularly by finance-constrained SMEs.

# 6.4 Regional policy priorities

For ECA’s EU economies, private and public investment will benefit from the phasing in of projects financed by EU funds. The EU’s National Recovery and Resilience Plans (NRRPs), which are supported by the largest funding package ever approved by the EU, provide a unique opportunity to promote economic recovery as well as green and digital infrastructure, and to help close investment and income gaps with more advanced EU members. In all, NextGenerationEU funds to support the NRRPs amount to 9.3 percent of 2021 GDP in Bulgaria, 11.0 percent in Croatia, 6.3 percent in Poland, and 12.1 percent in Romania—much larger than the EU average of 5.6 percent. Since the passage of the NRRPs, private investment prospects have also improved. In Bulgaria— the EU’s poorest economy, where output per capita is only about 55 percent of the EU average—private-