rafmacalaba/data-use-mentions-extended huggingface dataset:
engines like Google Dataset Search, increasing reach and accessibility. Since the CVs for this schema are under development, we recommend that early adopters use free text fields after “other” options to collect information for potential expansions or modifications to the CVs.<sup>14</sup> Finally, _user accounts_ allow contributors to track and edit catalog entries after they have been posted, data owners to claim entries, and front-end users to save searches or individual records, while a _data review system_ contributes to ensuring data quality control and avoiding version control issues, duplication of entries, or so-called “ghost entries”. For this purpose, incomplete entries could be regularly flagged for purging.

**Back-end:** The data entry interface for contributors should minimize the time and effort (and hence potential for errors) required to complete an entry to help maintain data quality. This includes making use of existing information where available. Especially for bulk entry of existing RCT data, a sophisticated implementation could draw on existing public records where available, such as the API interfaces of ClinicalTrials.gov and the World Bank Microdata Catalog,<sup>15</sup> , or the downloadable AEA RCT Registry data. New catalog entries could also be partially pre-filled by scraping web data from external resources such as registry entries and academic articles. This could best be achieved by beginning the data entry with the links to (some) external resources (which would also permit a duplication check within the catalog).

Within a metadata entry, information filled early on can provide inputs to later fields, such as pre-filling the treatment arms that were recorded in the “outcomes and interventions” section (III) in the “data” section (V). The catalog can also prompt contributors for information based on earlier inputs, such as suggesting entries for ethics documentation (section VI) or prior studies (section IV) in the “external resources” section VII. Automated cross-checks and data validation can additionally be applied to numeric and multiple-choice
An internal migrant is defined as an individual who has left the governorate of residence since birth in order to live in another region/governorate.<sup>3</sup> The internal migration rate is calculated as a ratio of the number of migrants to that of the total population.

Although Egypt’s economy is in a transitional phase, internal migration has lessened rather than increased. Internal migration rates declined during the 1970s, but stabilized since the mid2000s, oscillating around 4% between 2007 and 2009, and reaching 6.1 percent in Q1 2010 (see Figure 1).

Figure 1 – Internal Migration Rate in Egypt <!-- Start of picture text --> Internal Migration Rate - Egypt<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>1976 1986 1996 2006 Q1 2007 Q2 2007 Q3 2007 Q4 2007 Q1 2008 Q2 2008 Q3 2008 Q4 2008 Q1 2009 Q2 2009 Q3 2009 Q4 2009 Q1 2010<br><!-- End of picture text --> Source: CAPMAS and authors’ calculations using Labor Force Survey Egypt’s internal migration rates have not only declined over time, they are low by international standards. The world average internal migration rate as a share of working-age population is around 15 percent, while in Egypt it is 8 percent (see Figure 2).

> 3 Egypt is divided into 28 governorates.

3
# REFORMING TAx SYSTEMS: Ti-E WORLD BANK RECORD IN THE 1990s

This review of Bank projects in the 1990s with tax or customs administration components aims to analyze the extent and nature of their institutional focus. A second objective is to identify and assess the performance indicators used. The purpose of the review is to draw lessons for future Bank work in the area of tax systems advice.

The paper discussed the rationale for involvement in tax reform; the nature of pre-project diagnostic work in projects; the composition of the 83 projects with tax systems components; key features of project design; the nature of performance indicators specified in projects; project appraisal; selected aspects of project implementation; and evaluation of project outcomes. Conclusions and suggestions for future Bank loans for administrative reform are then offered.

## 1. **The Why: Rationale for Bank Lending for Tax Systems Reform**

The corporate objective of the World Bank group is to reduce world poverty. Growth and macroeconomic stability are necessary pre-conditions to reduce poverty. The need to strengthen revenue generation has traditionally been a self-eviden **t** ask of development, which the Bank has chosen to pursue with a variety of means.

Whereas policy advice on revenue architecture has been and continues to be a prominent part of the Bank's analytical support to countries, there has been increasing realization that good policies alone are insufficient for sustained, reliable revenue generation, which in turn is a necessary condition for both macroeconomic stability and provision of adequate social services by the Government. In the medium to long term, evidence shows that strong institutions, particularly institutions of governance are as if not more importan **t** o achieve sustained growth and poverty reduction. There is also some evidence showing that this applies to revenue generation. Good institutions in government ensure effective policy making, accountability for their actions of the government and its functionaries to citizens, and effective and efficient service delivery. Key requirements for these outcomes are transparent procedures, mechanisms to involve citizens in decision making and evaluation
Two instrumental variables (IV) are used. The first one is the trust score from the EIU database. This indicator considers how confident respondents are that their activity online is private. The score takes values from 0 to 100, where 100 is the most inclusive environment (The Economist Intelligence Unit, 2021a). The existence of such environment would encourage women and girls to access the internet, closing the gender gap in accessing internet with no direct effect on labor force participation. The second IV is the percentage of schools with internet access. This variable is used to control for internet availability. Increasing internet availability in an area would increase women’s access to the internet (Kusumawardhani et al, 2023).

# **4. Estimated Results**

The estimated coefficients of the different models are presented in Table 2. The first column represents the results of the GLS model ( _Model 1_ ) of the Internet Inclusion Index as the main independent variable. The Internet Inclusion Index has a positive significant impact on the gender gap in the labor force. This means that an inclusive internet environment is associated with higher ratio of female-to-male labor force participation.

Considering the gender gap in accessing the internet ( _Model 2_ ), the results show that when men have greater access to the internet than women (indicated by a higher positive value of the index of gender gap in access to internet), the female to male labor force participation ratio decreases. However, this negative effect is not significant in the GLS model. In the 2SLS model ( _Model 3_ ), in contrast, when instrumenting the gender gap in internet access with the trust score and the percentage of schools with internet access, this negative effect is significant. These results align with the proposition that, accessing the internet is a necessary but not sufficient condition for women to access economic opportunities. It worth noting that the results of the first stage of the 2SLS model<sup>5</sup> showed that the higher the trust score value and the
OZIER - REPLICATION REDUX – p. 35 of 41

# 5. References

AEA, 2018. _“AEA RCT Registry.”_ Available at: <u>https://www.socialscienceregistry.org/site/about (accessed March 16,</u> 2018) Ahuja, A., Baird, B., Hicks, J. H., Kremer M., and Miguel, E., 2017. “Economics of Mass Deworming Programs.” _Disease Control Priorities_ .

Aiken, A.M., Davey, C., Hayes R.J., and Hargreaves, J., 2013. Deworming schoolchildren in Kenya ‐ Replication plan. International Institute Impact Evaluation (3ie) Available at: <u>http://www.3ieimpact.org/media/filer_public/2013/05/14/aiken_replication_plan_final.pdf (accessed March 5,</u> 2018) Aiken, A.M., Davey C., Hargreaves, J., and Hayes R.J., 2014. “Reanalysis of health and educational impacts of a school‐based deworming program in western Kenya: Part 1, pure replication”, 3ie Replication Paper 3, part 1. Washington, DC: International Initiative for Impact Evaluation (3ie). Available at: <u>http://www.3ieimpact.org/media/filer_public/2015/01/07/3ie_rps3_worms_replication_1.pdf</u> (accessed March 9, 2018) Aiken, A.M., Davey, C., Hargreaves, J., and Hayes R.J., 2015. “Reanalysis of health and educational impacts of a school‐based deworming program in western Kenya: a pure replication”, _International Journal of Epidemiology_ , 2015 44(5):1572‐1580 Allcott, H., 2015. “Site selection bias in program evaluation,” _Quarterly Journal of Economics,_ 130(3):1117‐1165 Anderson,
one<br>disaggregation.|
|18||Resource Use|(18.1) Data on fishery harvests;<br>(18.2) Data on timber harvests<br>or deforestation;<br>(18.3) Data on major mining or<br>extractive activities;<br>(18.4) Water supply and/ or<br>consumption.|(18.1, 18.2) None<br>(18.3) Type of mining activity;<br>(18.4) None|To receive full point: Must have three indicators,<br>disaggregated<br>To receive half point: Must have two indicators, disaggregated|
|19<br>||Energy Use<br>|(19.1) Energy consumption<br>|(19.1) Energy type; end-use<br>sector; industrial sector.<br>|To receive full point: Must have (19.1) by energy type and<br>one other disaggregation. Three energy types must be present.<br>To receive half point: Must have (19.1) by energy type and one<br>other disaggregation. Two energytypes must bepresent.<br> **Table A3 continued**|

39
Policy Research Working Paper 10301

# **Abstract**

Despite the relevance of house prices for a variety of stakeholders as well as for macroeconomic and monetary policy making, reliable, publicly available house price data are largely absent in emerging markets and developing economies. Filling this void, this paper presents a systematic approach to collecting, analyzing, and assessing private property prices in emerging markets and developing economies. The paper uses data scraped from five countries’ largest real estate websites where private properties are listed for sale, to obtain price data and property attributes to establish a comprehensive data set that allows for both intra- and inter-country comparison of residential property prices. It then outlines the usability of these data by employing random forest estimation to predict the price of a standard housing unit—the basic house price—that is comparable across countries. While this approach is also applicable to filling wide data gaps in the provision of private property prices in developed economies, the paper focuses on how this approach can be applied to emerging markets and developing economies, where private property price data are particularly scarce.

This paper is a product of the Development Impact Measurement Department, International Finance Corporation. It is part of a larger effort by the World Bank Group 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 dbehr@worldbank.org; khaider@ifc.org; ssingh13@ifc.org; and azaman@ifc.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
the destination country. Furthermore, as an alternative and to check for robustness, we construct a novel proxy of digital tourism platform adoption, based on _Google Trends_ data, to get a more direct look at the use of digital tools for tourism purposes.

Before describing our model, data and econometric results in more detail, the next section provides further information on the evolution of tourism trends, its relevance for development outcomes, and the increasing use of digital tools in travel and tourism activities. We pay particular attention to countries in the Middle East and North Africa (MENA) and in Sub‐Saharan Africa (SSA), as the countries in the two regions have only recently been catching up with the rest of the world in terms of the use of digital tools, with a presumption that there is untapped potential to leverage the new technologies and help create more jobs.

# **2. International tourism and the digital economy**

## **2.1 Tourism matters for development**

Tourism represents over 10% of global GDP, it is the second‐fastest growing industry in attracting FDI, and it is the second‐largest job creator, supporting 292 million jobs by the end of 2016 (International Finance Corporation, 2017). There is a strong correlation between tourist arrivals and employment and GDP in the travel and tourism industry: a 10‐percent increase in arrivals translates into a 6.3 percent increase in jobs in the industry, and a 10 percent increase in travel‐and‐tourism GDP (Figure 1).

There is evidence of a causal impact as well. Arezki et al (2009) estimate growth equations that incorporate measures of tourism specialization. The authors use information from UNESCO’s World Heritage List to construct an instrumental variable for tourism and apply it to a cross‐section of countries for the period 1980–2002. They find that tourism specialization is positively correlated with economic growth, with a one standard‐deviation increase in the share of tourism in exports
: T-Statistics in parentheses. * :significant at 10% level, **:significant at 5% level

# **IV.2 Investment**

Our results for investment seem less robust to specification. We still use the three monthly deposit rate as a proxy of the opportunity cost of funds, due to the lack of reliable lending rate data. Although the levels of lending and deposit rates are different, the variation in the deposit rate would be expected to track the variation in the lending rate reasonably well. The results of the basic equation estimation for private fixed capital formation are in the first two columns of Table 12. Though the capital account does not significantly affect private fixed capital formation whether real M2 is included or not, the real interest rate becomes significantly negative only when it is included. But the sign of the coefficient of real M2 is negative, which is not plausible. The results for fixed capital formation by the public sector, as shown in the last two columns of Table 11 are not different. Capital flows do not significantly enter any of the two equations, while the implausible sign on real M2 persists.

Error correction versions of the estimation are summarized in Table 13. It can seen that public investment still is not related to capital flows, but capital flows, in past level, or past changes, do effect private fixed capital formation. Based on the error correction
‐olds across countries), either seeking to control for confounders in regressions (OECD 2014) or by using age‐cutoffs for grade enrollment to exogenously identify differences (Strom 2004; Frenette 2008; Benton 2014; Khaw and Wong 2012; Lau and Wong 2013; Marchionni and Vazquez 2015). Neither of these methods maps out a trajectory beyond two years, whereas skills may accumulate at different rates over the primary school cycle.<sup>7</sup> A few other tests assess reading and numeracy competencies of children in a wide age range, but the content of the tests is set at the level of early grades and provides limited information on the learning trajectory of later years in the education cycle. For example, the Annual State of Education Report (ASER) in India and Pakistan, Uwezo in East Africa, and the Independent Measurement of Learning (MIA) in Mexico test the basic reading and numeracy skills of children aged between 5 and 16 through household‐ based assessments. In addition, these tests are based on national curricula to guide domestic policy dialogue and are not necessarily comparable across countries (PAL Network 2017). Similar constraints apply to the Early Grade Reading Assessment (EGRA) and the Early Grade Math Assessment (EGMA), which have been widely used in Africa, the Middle East and South Asia (RTI International 2009).

In this paper, we use an adult skill assessment to estimate the relationship between learning gains throughout the primary cycle. The advantage of using adults is that the analysis avoids selection in terms of who has achieved a certain grade by a certain age. Selection in total years of schooling remains, to a degree that varies by the estimation method. We employ two alternative methods to estimate the EYOS associated with one standard deviation in learning. The first uses simple descriptive data to characterize 7 Another, related effort seeks to combine the quality and quantity of education into a single cross‐country measure – the Learning Adjusted Years of Schooling, or LAYS – to allow
the results. The exposure variables are measured in real U.S. dollars (normalized with the consumer price index). We drop all workers who are younger than 15 years old from the sample. When calculating the trade exposure index, we include all individuals who reported an industry for their main activity. The reported industries of individuals in the labor force survey are mapped to the ISIC 3.1 industry codes at the 4-digit level so that the trade data can be merged with the labor data. When calculating the average wage and informality probability, we restrict the sample to the individuals who reported weekly wages larger than 100 takas.

# Methodology

This paper combines both the local labor market approach characterized by Bartik (1991) with an approach designed to generate evidence that can be compared with the long-run general equilibrium predictions described earlier.

Short Run Local Labor Market Effects of Positive Export Shocks To estimate the relationship between exports and local labor market outcomes, we follow an unbiased econometric approach commonly employed in the literature to assess how exports affect workers in Bangladesh. Our starting point is that the impact of a trade shock should differ across regions, depending on the industry composition of each sub-district. For instance, let us imagine a trade shock especially prominent for a particular sector, regions where employment is more concentrated in that sector will be more affected. In this regard, differences in exposure of regions to this shock serves as an identification tool. A fundamental principle in this approach is existence of segmented labor markets. Identifiable labor mobility barriers or rigidities, such as commuting costs or lack of transport infrastructure, allows us to predict variations in local labor market outcomes and to estimate the effects of different exposure to trade.

We need to address potential endogeneity in trade exposure covariate. Since we observe changes in labor outcomes and exports simultaneously, we cannot identify which causes the other; an exogenous source of variation is required to determine direction of causality. Artuc et al. (2019) propose a strategy to estimate how an exogenous demand shock
**Figures 5:  Distribution of Countries by (Relative) Income Classification, 1900-2008, %**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>>0.7<br>60<br>0.5 to 0.7<br>50<br>0.3 to 0.5<br>40<br>30 0.1 to 0.3<br>20 <0.1<br>10<br>0<br>1900 1950 1960 1970 1980 1990 2000 2008<br><!-- End of picture text --> Source: Authors‘ calculations based on Maddison data.

There is also some ―churning‖ where countries not only converge up the ladder, but also diverge down the ladder. This is the case of some former colonies in Africa: many have gone from being lower MICs at independence to LICs in 1980. Since then, some have climbed back up to MIC status. There are also countries at the HIC end of the distribution that have fallen back to MIC status, by this measure.<sup>5</sup> Many middle-income countries face the risk of falling into a middle income trap. Even some previously high growth Asian economies, like Malaysia and Thailand,<sup>6</sup> experienced a substantial deceleration of growth following the Asian financial crisis. The Latin America and Caribbean region, however, probably provides the classic example of MICs failing to progress to high income country status. Figure 6 reveals the persistent lack of convergence of the Latin America region with living standards in the United States. Periods of mild catch-up were followed by periods of declining relative incomes. More recently, most of the economies of Latin America have stabilized and there has been a strong upturn in growth, led by the largest economy of the region—Brazil—as will be discussed in more detail in the
ratios, namely the 90/10 ratio, the 80/20 ratio, and the Palma ratio (90/40 ratio). All income measures are converted to real terms using 2011 Purchasing Power Parity (PPP) dollars for comparison across survey years.

We also employ Gini data from different sources available at the country level. The first is taken from the World Bank Poverty and Inequality Platform (PIP). The data are based on primary household surveys obtained from government statistical agencies and World Bank country departments. In the case of high-income economies, they are mostly derived from the

> 14 To illustrate, we fix the poverty line for all regions in our sample and identify a region as poor if its gross income (per day) is below the poverty line.

64
# **1. Introduction**

High and potentially downward rigid reservation wages – below which unemployed persons would not accept a job – may be a key reason for high and persistent unemployment rates. North Macedonia’s unemployment rate currently stands at 20.8%, though it has continued to decline since its peak of 36% in 2006. The decline – especially during the Global Financial Crisis - has been mainly driven by the government-supported expansion of foreign production capacities in the country and frequentlygenerous programs for subsidizing employment, though also potentially interfering with the absence of a census since 2002 and the accelerated emigration from the country since then. The level of the unemployment rate in North Macedonia also reflects structural characteristics of the labor force: a large share of low-skilled job seekers, accompanied by sizable skill mismatches, prevents fast and smooth transition to decent employment.

Still, the role of reservation wage for unemployment should be viewed in at least two important aspects. First, there is almost no evidence about the trend of reservation wages, nor about the way of their formation given personal and labor-market circumstances. The reservation wage in nationallyrepresentative surveys – like the Labor Force Survey – has been asked only in 2016, making the exploration of the job-search relationship between reservation wage, personal traits and institutional aspects (e.g. the generosity of the unemployment benefits) difficult so far. Second, despite the level and structural characteristics of unemployment in the country, still the decline in a decade has been sizable.

This paper has two objectives: first, to understand the determinants of reservation wages in North Macedonia; and second, to measure the gap between reservation and market wages. Both will enable understanding of the formation of reservation wages and its importance for tailoring of policies to alleviate its potentially adverse role for unemployment. We rely on two years of the Labor Force Survey – 2016 and 2017, despite maintaining only a pooled cross-section structure due to the short period on disposal. Given the constraints, the approach is only exploratory in nature,