rafmacalaba/datause-encoder-data huggingface dataset:
Table 18 – Access to Technology and Rates of Return

|ROR (2006)|With PC|Without PC|
|---|---|---|
|Voc. Sec. Industrial(3-Yrs)|10%|3.18%|
|Voc. Sec. Commerce & Other(3-Yrs)|14%|4.12%|
|Vocational Sec. (5-Yrs)|26%|5.40%|
|University (4-Yrs)|13%|7.44%|
|Post Graduate|26%|7.32%|

These results point to the importance of technology in education. In principle, they suggest the relevance of building school computer labs, supplying computers, and connectivity in schools. This will necessarily imply developing and disseminating new curricula in electronic format. Distance learning programs wil also become essential elements.

However, providing computers and technology is no guarantee that the quality of education will improve. Evaluations of these programs show mixed results, especially in developing economies. For instance, an impact evaluation of the use of computers in education in Colombia showed that teachers used the computers for class preparation and to teach students computer skills in the presentation and dissemination of information, rather than for the intended purpose of developing new knowledge in language and mathematics (Barrera and Linden, 2009). Hence, the introduction of technology will not affect education unless teachers are trained and develop new skills in the use of the new technology. Incorporating technology in the learning process requires more than computers in the classroom.

# **VI. Conclusions and Directions for Future Research**

The rate of return to investment in education in Egypt varies depending on the specific path into which the individual is sorted. Individuals who are sorted into the general secondary-university path earn higher rates of return to education. This fact perpetuates inequality.

Other factors are sources of heterogeneity: returns to education increase with firm size, female returns to education tend to be larger, and the factors affecting their participation in the labor market are different than for males. Finally, access to technology produces the largest discrepancy in RoR across individuals, with the RoR being two to four times larger for individuals with access to computers. This result highlights the importance of modifying the curriculum to include more computer access in schools, with corresponding monitoring and evaluation of the use of computers in the classroom.

Other interesting results of this paper: (a) Workers in the formal market earn more than informal workers, but in the past this was the opposite. (b) Regarding the relationship between government and private sector workers, there are major differences depending on gender. While males in the private sector earn a 25 percent premium with respect to government employees, females in the government sector earn the same as in the private sector. This is a clear incentive for females to wait in queue for a government job, as it sets a reservation wage. This might explain why female unemployment is higher than that for males. (c) Regional wage premiums have reduced significantly or disappeared. At the end 18
Policy Research Working Paper 10581

# **Abstract**

This paper presents a coping strategy that small-scale cross-border traders adopted in response to the shock of the COVID-19 pandemic and examines its impact. Using a cross-sectional data set of 1,159 traders from the borderlands of the Democratic Republic of Congo and Rwanda, the paper assesses the impact of adopting the Cluster Trading Approach on trade outcomes, household income and poverty reduction. When applying a local average treatment effect approach, the findings reveal that adoption of the CTA causes at least 21 and 31 percentage point increases in traders’ turnover and profit respectively. The household income analysis and poverty decomposition highlight an increase in income, even within the depth and severity of poverty. Thus, although access to capital is important for small-scale cross-border traders joining a cluster according to the literature, the results show that the level of capital is less important for income increase once there. As the results are robust to competing explanations and heterogeneity of the sample, the paper concludes that the Cluster Trading Approach is a poverty-reducing strategy and discusses the challenges for its sustainability.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at ckunaka@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
heterogeneity. Findings suggest that country-level characteristics—including public spending efficiency and capital scarcity—are relevant, as well as macroeconomic factors. Methodological and sample differences may also explain some variation in results across studies. That said, the evidence on the impact of public investment to growth in EMDEs is relatively meagre, owing in large part to associated data constraints. Thus, further research—including that provided in this paper—is needed to better inform how public investment can stimulate economic growth and mobilize private investment.

# **3. Methodology and data**

## **3.1. Data and sample**

The database used in the estimation of the macroeconomic effects of public investment draws from several sources. Public investment, private investment, and capital stock data are from the International Monetary Fund’s Investment and Capital Stock Dataset (IMF 2021a). Public debt data are retrieved from the World Bank’s Fiscal Space Database (Kose et al. 2022). Public investment efficiency data are obtained from several sources: IMF (2021b) Fiscal Monitor database, Devadas and Pennings (2018), and Dabla-Norris et al. (2012). Potential output data are sourced from Kilic Celik et al. (2023). GDP and inflation series are from the IMF’s World Economic Outlook database. Labor productivity and total factor productivity data are from Penn World Table 10.01. The resulting dataset comprises up to 129 EMDEs, spanning the period 19802019 (see Appendix table A1 for the sample composition).<sup>12</sup>

## **3.2. A new approach to identify public investment shocks based on cyclically adjusted public spending**

In this paper we apply a new approach to identify public investment shocks. The methodology builds on the work of Alesina et al. (1998), Alesina and Ardagna (2010), and related studies that assess the macroeconomic effects of changes in cyclically adjusted fiscal variables. Conceptually, the approach is consistent with the literature arguing that large and apparent scaling up of public investment tends to reflect exogenous decisions by the public authorities (Deleidi et al. 2020; Warner 2014). The shock identification framework involves four steps:

- First, we estimate output elasticities of public investment for each country in the sample by regressing the logarithm of real public investment on the logarithm of real GDP. Estimates are done using ordinary least squares for each country with at least 20 continuous observations of both variables.<sup>13</sup>

> 12 The sample composition and time coverage are determined entirely by the data availability. In particular, the current version of the Investment and Capital Stock Dataset (IMF 2021a), providing consistent disaggregated series for public and private investment, covers the period 1960-2019.

> 13 Countries with fewer than 20 continuous observations were not included in the sample going forward.

9
social protection may seem insufficient right now, it is clear that the challenge in the medium and long terms will be more serious and will require substantial reforms to be designed and applied in the short term.

Therefore, the purpose of this work is, first, to look into the performance of the income protection system for older people as a whole, taking into account both mentioned pillars, that is to say, the contributory and the non-contributory pension schemes. Second, to understand the challenges involved in the medium and long terms posed by the demographic transition, particularly in relation to financial sustainability in the IESS-managed contributory system.

The structure of this document is the following: Next section relates to the historical progression of the design of the income protection system for older people. The third section presents and discusses different indicators related to the performance of current pension schemes and impact thereof on poverty and income distribution. The fourth section makes an actuarial simulation by means of the World Bank Pension Reform Options Simulation Toolkit, which allows simulating income and expenditure paths in IESS pension insurance. Finally, there is a final conclusion section.

# 2. Literature Review: Historical evolution of the pension system

The pension system in Ecuador, as it is right now, is far from having consolidated over time. Just as in the rest of the region, the social protection system and related different components have been extensively modified from their initial conception.

In Ecuador, there was a first approach in 1928 with _Ley de Jubilación y Montepío, Ahorro y Cooperativas_ (Law of Retirement and Assistance Fund, Savings and Cooperatives), that gave birth to the Pension Fund. Being corporatist and independent from the government, this fund aimed at providing retirement pensions, funerary assistance and widow pensions to public servants, civilians and military officers (Ibarra-Jarrin, 2015; Valverde, 2008; Sasso, 2011). Further that same year, this insurance extended to cover also banking employees. In 1935, the _Seguro General Obligatorio_ (SGO, acronym in Spanish) (Compulsory General Insurance) was created, and the _Instituto Nacional de Prevision_ (National Social Security Institute) was created as the top social insurance body covering both public servants and private employees. The two-part contribution system was established with compulsory individual contributions ranging from 5% to 10% of wages, and a similar employer contribution (Galvis Muñoz, 2015). In the next decade, under Carlos Arroyo del Rio's administration, the state's contribution was 3
# **3. What Lies Ahead**

Our approach to impact forecasting incorporates projected socioeconomic and demographic trends as well as climate change. This requires us to adopt internallyconsistent assumptions about future changes in emissions, economies, human development levels and populations. The emissions scenario leads to a forecast of greenhouse gas concentration in the atmosphere, which is related to changes in global and local climate through one of a large number of global circulation models (GCMs). For the economic forecast, we draw on a recent summary of integrated assessment models by Hughes (2009), who draws on a critical assessment of the IPCC’s SRES scenarios by Tol, et al. (2005). Hughes develops a consensus economic projection by taking an average growth rate from three major integrated assessment models:<sup>3</sup> Climate Framework for Uncertainty, Negotiation, and Distribution (Anthoff and Tol, 2008); PAGE2002 (Hope, 2006); and Regional Dynamic Integrated Model of Climate and the Economy (Nordhaus and Boyer, 2000). We use Hughes’ constant-dollar GDP series, because our econometric risk estimation requires the use of data extending back to 1960.

For the population forecast (which includes projections of life expectancies and total fertility rates), we use the UN’s Medium Variant Projection (2006 Revision). Because our economic projections incorporate interactions with projected climate change, they are moderate in their view of future prospects. Overall, the economic and demographic projections we employ are relatively close to those in the SRES A2 Scenario.<sup>4</sup> We attempt to bound the set of reasonable expectations about future climate using GCMs with strongly-contrasting predictions. Within the SRES A2 scenario, the GCMs provide a relatively uniform view of future increases in temperature. However, this is not the

> 3  Using an average growth rate for the three major integrated assessment models greatly simplifies the econometric simulation work in this paper, which would otherwise require comparison of complex runs for three different macro-scenarios.  Use of the average also ensures consistency with the IPCC A2 scenario which, as we note above, incorporates a nearly-identical growth rate.

> 4  IPCC (2000) characterizes A2 as follows: “A very heterogeneous world, characterized by self-reliance and preservation of local identities. Fertility patterns across regions converge very slowly, which results in high population growth. Economic development is primarily regionally oriented and per capita economic growth and technological change are more fragmented and slower than in other scenarios.”

6
(income, education, etc.), establishing institutional mechanisms for rural electrification, providing inputs to power sector reform, formulating guidelines for tariffs, subsidies, and others. Among the multiple objectives, making a positive impact on the livelihood of rural people is the foremost. However, without proper assessment of such projects it is impossible to determine if, and to what extent, these objectives are achieved.

Although there have been many general studies on rural electrification as it relates to development (Barnes, Peskin and Fitzgerald 2003; Barnes 1988; Butler, Poe and Tendler 1980; Fluitman 1983; Saunders and others 1975), there have not been many systematic impact studies of particular rural electrification projects and this includes Vietnam. Most of the past evaluation works on specific rural electrification projects has concentrated on project outputs (for example, number of communities or households connected). Such assessments usually do not measure the nature and extent of the accrued benefits, let alone establish the causality as to whether the measured benefits are attributable to electrification.

In recent years the World Bank initiated impact studies and monitoring and evaluation (M&E) of its own projects. This paper investigates impacts of the World Bank financed Rural Electrification project (REI) in Vietnam on household welfare using panel surveys fielded in 2002 and 2005. The survey data covered communes already having electricity, those that would receive electricity under the RE project, and areas which were not scheduled to receive electricity within a 5 year time frame and hence are treated as control. However, in few survey areas electricity has been provided by non-World Bank entities. So, besides estimating the impacts of rural electrification, this study also investigates if impacts are different for project (World Bank-implemented) and nonproject electrification. Using rigorous estimation techniques, this study estimates the benefits of both commune and household electrification.

3
Panel B shows that Size and Age are positively correlated, suggesting that older firms are larger in our sample. Establishment Size Ratio and Age are also positively correlated, suggesting that firms grow as they age.

Our cross-country data are subject to some caveats. First, the Enterprise Surveys sample only the formal sector in each country and exclude the informal sector. In addition, since the sampling frame is restricted to 5 employees or above, our results do not speak to the micro enterprises.

Second, our data are only on the continuing/surviving firms and hence we have no data on firm exit rates. On a related note, the surveys are stratified only by industry, firm size, and geographical location and so we may not have a completely representative sample of firm ages, though the firms within the strata are randomly sampled.

Third, our analysis is at the establishment level and not at the firm level since the sampling unit in the Enterprise Surveys is the establishment.<sup>11</sup> While this has the advantage that our employment measures are well defined and capture actual jobs at the establishment rather than changes from mergers, acquisitions, and divestitures, we are not able to measure firm size accurately for multi-establishment firms. However we are helped to some extent that the establishments in our sample report whether they are part of a larger firm or whether they are stand-alone. While most of the establishments in our data are stand-alone establishments (86%) and hence can be treated as firms, for robustness, we repeat the analysis on the sub-sample of firms that report that they have a single establishment and find that all our results hold.

> 11 In the Enterprise Surveys, the establishment is defined as a physical location where business is carried out and where industrial operations take place or services are provided. In addition, an establishment must make its own financial decisions, have its own financial statements separate from those of the firm, and have its own management and control over its payroll.

11
Savings from the reductions in thermal energy and electricity use are represented by (Ht) and (Et) respectively, with the kindergarten year as ( _t)_ , where ( _i)_ represents the 6 percent discount rate for human development projects, and (N) is the operation period of the kindergarten (in the project in question, it is up to 50 years).

We used the following formula to calculate Ht and Et: ), tt HHtt aa bb aa bb HH = ττ ∗(SS −SS ) ∗(εε −εε ) tt BBtt aa bb aa bb Established tariffs for thermal energy and electricity are represented by (MM = ττ ∗(SS −SS ) ∗(μμ −μμ and ) HHtt BBtt respectively, the year is represented by ( _t)_ (RUR/10<sup>9</sup> calories), and (Sa – Sττ b) is the ττ difference in the heated floor areas between the Semitsvetik kindergarten (4,713.1 square meters) and the proposed energy-efficient kindergarten (3,238 square meters). (εa – εb) and (μa – μb) represent the differences in thermal energy and electricity consumption respectively (per square meter) between the Semitsvetik kindergarten and the proposed kindergarten. The results of these calculations are presented in Table 4.

**Table 4: Total Benefits from Investing in the Construction of an Energy-efficient Kindergarten in Khanty-Mansyisk under Three Scenarios**

|Scenario|Operation<br>thermal energy|s costs<br>Electricity|Savings (over 50<br>million RUR,|years),<br> US$|**Savings (RUR**<br>**perplace), %**|
|---|---|---|---|---|---|
|(1)|(2)|(3)|(4)|(5)|(6)|
|High (as designed)|70%|44%|70.2|2.2|**28.3%**|
|Moderate|50%|22%|46.1|1.4|**18.1%**|
|Low|30%|11%|41.1|1.3|**10.3%**|

_Source_ : Authors’ calculations We found that proper design and project planning can save up to RUR 70.2 million 24
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