rafmacalaba/datause-encoder-data huggingface dataset:
46

- De Long, Bradford and Laurence H. Summers, 1991, "Equipment investnent and economic growth," Quarterly Jniirnal of Fconomics, 106, pp. 445-502.

# Denison, 1967, Why growth rates differ, Brookings Institution: Washington DC.

- Easterly, William, Michael Kremer, Lant Pritchett, and Lawrence Summers, 1993, "Good policy or good luck? Country growth performance and temporary shocks," Ioiirnal of Mnnetary Fconnmic, 32(3), pp. 417458.

# Easterly, William and Ross Levine, 1995, "The African growth tragedy," mimeo.

- Elley, Warwick, 1992, 1How in the world do students reand?, International Association for the Evaluation of Educational Attainment.

Fogel, Robert, 1994, "

- Foster, Andrew D. and Mark R. Rosenzweig, 1994, uTechnical change and human capital returns and investments: Consequences of the Green Revolution," mitneo (August).

# Funkhouser, Edward, 1994, "The returns to education in Central America," mimeo (December).

- Gelb, Alan, J.K. Knight, and Richard H. Sabot, 1991, "Public sector employment, rent seeking, and economic growth," Fonnnmic JmiIrnal, 1Ol(Sept.), pp 1186-1199.

- Gersovitz, Mark and Christina Paxson, 1995, 'The revenues and expenditures of African governments: Modalities and consequences," mimneo.

- Glewwe, Paul, 1991, "Schooling, skills, and the returns to government investment in education," Living Standards Measurement Survey Working Paper 76.

- Glewwe, Paul, 1995, "How does schooling of mothers improve child health: Evidence from Morocco," mimeo (January).

- Hanushek, Eric, 1986, "The economics of schooling: Production and efficiency in public schools," kimnal of Fcnnomic T iterahlre, 24(3), pp. 1141-1177.

- Hanushek, Eric, 1995, "Interpreting recent research on schooling in developing countries," Wnrld Rankl Recearch Ohserver.

- Hobcraft, J., 1993, "Women's education, child welfare, and child survival: A review of the evidence," The 14ealth Trancgition Review, 3(2), pp. 159-175.

- Jamison, Dean and Lawrence Lau, 1982, Farmer F.duratinn and Fnrm Efficienry, Johns Hopkins: Baltimore.

- Jones, Chad, 1995, 'R&D based models of economic growth," rnurnal nf Pnliticral Fronnnmy, (forthcoming) August, 1995.
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labor cost relative to revenues; that is, more influential firms on average have a lower relative share of employment costs.<sup>45</sup> How do our estimates of Political Influence compare to the direct measure of connections included in the data? To facilitate this comparison, in Table 6, we provide the marginal effects of an increase of one standard deviation of political influence, a change of roughly 6.5 on the index.<sup>46</sup> These marginal effects are presented alongside the same marginal effect of having a political connection, compared to no such connection. Recall that our index is pinned to this political connection value, but the measurement model allows for finer differentiation of when such connections are more likely to result in more or less political influence. While the direct comparison of a 1 S.D. increase of the influence index and the marginal effect of having a political connection are not directly comparable, the table does provide a ready comparison of the two measures relative to the given outcomes.

Table 6: Marginal Effects of a 1 SD Increase in Political Influence Compared to Political Connections

|a. Fewer than 20 competitors (Y=100)|(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|Marginal Efect +1 SD in Index|2.384**|2.074**|1.826***|2.555***|2.442***|
|p-val.|0.013|0.017|0.013|0.001|0.001|
|Marginal Efect of Political Connection|6.453***|6.018***|8.464***|9.080***|33.96***|
|p-val.|0.006|0.010|0.001|0.002|0.009|
|b. Total Sales (log 2009 USD)||||||
|Marginal Efect +1 SD in Index|0.517***|0.470***|0.484***|0.478***|0.394***|
|p-val.|0.000|0.000|0.000|0.000|0.000|
|Marginal Efect of Political Connection|0.216***|0.146*|0.155*|0.243***|-0.508|
|p-val.|0.009|0.073|0.055|0.004|0.201|
|c. Sales per Worker (log 2009 USD)||||||
|Marginal Efect +1 SD in Index|0.156***|0.144***|0.156***|0.144***|0.102***|
|p-val.|0.000|0.000|0.000|0.000|0.000|
|Marginal Efect of Political Connection|-0.060|-0.067|-0.057|-0.001|-0.078|
|p-val.|0.274|0.269|0.279|0.989|0.655|
|d. Labor Costs to Sales Ratio (log)||||||
|Marginal Efect +1 SD in Index|-0.088***|-0.088***|-0.100***|-0.097***|-0.112***|
|p-val.|0.000|0.003|0.003|0.005|0.000|
|Marginal Efect of Political Connection|0.001|0.014|0.027|-0.026|0.237*|
|p-val.|0.989|0.796|0.651|0.614|0.067|
|**_X_** co-variates||✓|✓|✓||
|**_X_** interacted w/Pol. Infuence|||||✓|
|Location FEs|✓|✓|✓|by Sector|by Sector|
|Sector FEs|✓|✓|by Economy|by Location|by Location|

* _p <_ 0 _._ 10 ; ** _p <_ 0 _._ 05 ; *** _p <_ 0 _._ 01 OLS estimates. Robust standard errors, with two-way clustering at the 2-digit ISIC and region level in parentheses, per Cameron et al. (2011). Co-variates (not shown) include the log of age, the years of the manager’s experience, dummy variables for exporters, foreign-owned firms, and those part of a larger firm.

These results show that while political connections are related to a higher likelihood of having fewer

> 45See De Loecker et al. (2020) for an extensive discussion.

> 46This figure is average economy-level standard deviation across the 41 economies.

29
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expenses are to be incurred (Gadžo & Klemenčić 2017). However, these are far outweighed by the expected revenues as per the paper’s findings.<sup>12</sup> Information exchange should not be pursued in a vacuum or in isolation. Such policies should be framed in broader medium-term revenue strategies which would provide for ways to better leverage on information exchanged (these can be from the roll-out of risk-based tax auditing to data mining programs for instance). Equally, efforts to further deepen beneficial ownership registries/processes, or capacities to better capture transfer pricing can be equally important: they would provide further tools for using received data more efficiently.

Lastly, further analysis would be warranted on the political economy of tax cooperation. Reforms underpinning information exchange are key to international tax cooperation and ultimately tax justice. There are however questions about the drive and incentive for cooperation. In the case of Africa, estimates suggest that about 30 percent of Africans’ financial wealth is held offshore (Zucman 2015), providing a powerful drive for administrations to weed them out. Similarly, estimates presented here suggest a positive return to engaging in cooperation from a revenue standpoint. Departing from the fact that African countries are generally less efficient at converting income into taxation as opposed to OECD countries for instance, the marginal tax revenue unit is more valuable to them – thus placing an even higher value to returns from cooperation. Concurrently however, offshore assets are usually held by rich and powerful individuals with close ties to power – providing an important political disincentive (Grinberg, in Pogge and Mehta 2016). As shown in this paper, AEOI is taken up by countries with greater GDP growth, trade openness, financial development and government effectiveness, all of which tend to be correlated to higher governance and weaker constraints on political settlements for collective action. Delving further in the political economy would shed further light on conditions for more constrained countries to engage.

> 12 A review of budgets for technical assistance as provided by partners in the case of Senegal for AEOI compliance (including investments for servers, technical assistance etc.) confirms this comparison (AfDB 2019).

15
# 5. How to close the data gap?

# <u>Closing the data gap when surveys exist or can be collected</u>

The World Bank tries to play an active role in promoting access to household budget surveys. If data sharing is inhibited by lack of experience or capacity, governments can benefit from the World Bank’s experience in anonymization and protecting sensitive information; practices of data sharing from around the world that establish rules that govern microdata use and appropriate citation. The World Bank can provide training on preparation of metadata under the Data Documentation Initiative (DDI), an international standard for describing surveys. The World Bank should help support prioritization and advocate for these types of technical assistance (TA) to national statistics offices.

The World Bank can also play a role in promoting the value of open data by facilitating exchange of ideas and experiences within the region and beyond. Inviting leaders in the field to join regional workshops or conferences can help. The World Bank organized such a conference at the Centre for Mediterranean Integration (CMI) in 2016. Keynote speakers and high-level participants from national statistics offices across MENA discussed the challenges involved in collecting and sharing micro-data for monitoring welfare and for evidence-based policy making.<sup>11</sup> The World Bank also provides TA and funding to help countries conduct HBSs and measure poverty. This TA is typically offered through country-level programs, drawing on long-established country engagements. In several notable examples in MENA, World Bank collaboration with country statistical agencies was very fruitful and resulted in the dissemination of HBSs and publication of national poverty rates. These examples include TA on household surveys in Djibouti, Iraq, Jordan, West Bank and Gaza, and Yemen and on poverty measurement in Egypt, Tunisia, and Lebanon.

Collecting new HBS data and enhancing data sharing are very different in terms of costs. Given the analysis above, collecting new HBS data is more of a priority in MENA than is irregular poverty measurement. Nevertheless, data sharing should be an indispensable part of any international organization’s data collection effort.

If collection of a new household budget survey is limited by lack of funds, statistical agencies may consider using the methodology developed by the World Bank and called “Survey of well-being via instant and frequent tracking or SWIFT 2” (Yoshida et al. 2015). The main idea behind this method is the following. Instead of implementing a survey that collects a large sample of consumption data, the statistical agency can collect a nationally representative subsample of both consumption and non-consumption data and a much larger sample of non-consumption data only. Using the first sub-sample, which includes both consumption and non-consumption data, imputation models can be developed, and consumption can be imputed into each household in sub-sample 2.

> 11 Atamanov and Krishnan (2016).

12
Winters posits that neither of the polar extremes is likely to be precisely true and suggests the importance of determining the elasticity of labor supply in evaluating the supply response of unskilled workers. Thus, theoretical predictions with regard to the effects of trade on wages of unskilled workers are ambiguous, and the existence of S-S effects becomes an empirical question.

# (b) Data

# (i) The _Vietnam Household Living Standards Surveys_

The VHLSS 2002 and 2004 were conducted by the GSO of Vietnam with the technical support of the World Bank and are generally recognized to be of high quality and are representative of all of Vietnam. The VHLSS 2002 and 2004 consist of 30,000 households and 9,188 households respectively, and about half of the households interviewed for the VHLSS 2004 came from the sample of the VHLSS 2002. The timeframe of the VHLSS 2002 and 2004, which reflect information for the years 2001/2002 and 2003/2004 respectively, overlaps reasonably with the period when Vietnam’s exports to the U.S. expanded in the aftermath of the BTA (see Figure 2). During the same period, protection appears to have been still in place for import-competing production.<sup>23</sup> Thus, the focus of the paper is to evaluate the impacts of trade on wages on the export side.

Using the sampling weights available in the VHLSS 2004, out of 47.3 million people who had work in 2004 in Vietnam, about 14.6 million people (31.0 percent of total workers) held wage jobs of which 7.8 million (16.6 percent) and 6.8 million people (14.4 percent) worked in

> 23 For instance, the trade weighted Nominal Rate of Protection (NRP) for manufacturing was relatively high at 29.2 percent in 2003 (Athukorala, 2006, Table 3). Although the estimated Effective Rate of Protection (ERP) for manufacturing decreased from 95.9 percent in 2001 to 43.9 percent in 2003, the decline came from an increase in input tariff introduced to protect SOE engaged in intermediate production rather than from the decrease in tariff rates for final goods (Athukorala, 2006, p.174).

14
**International loans from non-resident banks to GDP** is equal to loans of BIS reporting banks to a specific country relative to economic activity.<sup>11</sup> **Off-shore deposit to domestic deposits** is the ratio of deposits held by a country’s nationals in off-shore banks relative to deposits in domestic banks. International loans increase in income level, while off-shore deposits to domestic deposits are highest for low-income countries and decrease in the income level of countries.  This can be partly explained by the lack of confidence that households and enterprises have in low income countries have in domestic banking systems, a phenomenon especially pronounced for countries in SubSaharan Africa (Honohan and Beck, 2007). There have been no clear trends over time in either international loans nor in off-shore deposits (Figure 21). Behind this lack of trends, however, is significant variation across income groups. While international loans have been increasing in highincome countries, they have been relatively stable in middle- and low-income countries. While offshort deposits relative to domestic deposits have been low and stable in high- and middle-income countries, they have halved in low-income countries between 1997 and 2007, from 4.9% to 2.4%.

Finally, **Remittance Inflows to GDP** measures the flow of official remittance flows relative to economic activity. With the increasing importance of migration flows, remittance flows have become an important source of capital inflows in many developing countries. In some countries, such as Tonga, Tajikistan, and Moldova remittance inflows surpass 30% of GDP, while they constitute 94% of GDP in Liberia. On average, however, the lower-middle income countries are the group with the highest ratio of remittances to GDP. Remittance flows have increased significantly over the past decades, from less than 1% in 1995 to almost 2% in 2007. This trend is driven by the doubling of remittance flows to low- and lower-middle income countries, while remittance flows to upper-middle and high-income countries have not shown a clear trend in recent years. These remittance patterns also reflect increasing migration flows from the developing to the developed world over the past years. These statistics, however, are most likely an underestimate of remittance flows, as they exclude informal flows, captured by the omitted category in balance of payments statistics.12

> 11 BIS reporting banks include banks residing in the G10 countries, Australia, Austria, the Bahamas, Bahrain, Bermuda, Brazil, the Cayman Islands, Chile, Chinese Taipei, Denmark, Finland, Greece, Guernsey, Hong Kong SAR, India, Ireland, Isle of Man, Jersey, Korea, Luxembourg, Macao SAR, Malaysia, Mexico, the Netherlands Antilles, Norway, Panama, Portugal, Singapore, Spain and Turkey.

> 12 According to estimates, at least a third of remittances is sent through informal channels (Freund and Spatafora, 2008; Celent, 2002).

13
We can take the average for all nodes to get a network-level measure, noting that this will grow with log( _N_ ) where _N_ equals the number of nodes. Moreover, for a network we have: A _triplet_ is a set of three connected nodes and a _closed triplet_ a set of three connected nodes where each one is connected with both others. _Geodesic distance_ is also called _shortest path length_ and the way the _clustering coefficient_ is calculated is called _transitivity_ .

In Figure 2 we give a simple illustration for two, stylized examples. On the left hand side, node A has degree 3; the distance to B is 1 (and is the same for C and D). The betweenness of A is 3 (viz., A is between BC, BD and CD). All the others have degree 1, distance to A, 1 and distance to others, 2 with betweenness 0. The network density is 3/12=25% and the clustering coefficient 0. For the right hand example, the betweenness of A becomes 0 (in fact, everyone’s betweenness becomes 0), the density is 6/12=50%, and the clustering becomes 1.

# **4.3 Network properties**

We turn to explicit consideration of the characteristics of networks. Specifically, we describe the extent and detail of connections running between individuals, as well as between individuals and institutions in the seven countries. As mentioned above, _PEPData_ documents the links that PEPs may have both with other individuals (including other PEPs), as well as with specific firms and political parties. We document the size and composition of the networks, paying particular attention to their components and extent of integration. We consider the extent to which these networks have dense or diffuse features along with evidence of small world properties, where clusters have the ability to link to other parts of the network through a limited number of bridges. The focus also falls on location in the network specifically in the context of centrality. These attributes are subsequently incorporated explicitly in the empirical analysis of Section 5.

12
# PPR \lorking.Raper Serwos

||idl|_Autho_||Contact<br>fQr papre|
|---|---|---|---|---|
|WPS308|Harmonizing Tax Policies in Central<br>Amerca|Yalcin M. Baran|November 1989|T. Watana<br>31882|
|WPS309|How to Improve Public Sector<br>Finances in Honduras|Yalcin M. Baran|November 1989|T. Watana<br>3' 882|
|WPS310|A Framework for Macroeconomic<br>Consistency for Zimbabwe|Ali Khadr<br>Klaus Schmidt-Hebbel|December 1989|S. Jonnakuty<br>61769|
|WPS311|Macroeconomic Performance<br>Before and After Disinflation in<br>Israel|Leonardo Leiderman<br>Nissan Liviatan|November 1989|R. Luz<br>61588|
|WPS312|Improving Public Enterprise<br>Performance: Lessons from<br>South Korea|Mary M. Shirley|October 1989|R. Malcolm<br>61708|
|WPS313|The Evolution of Paradigms of<br>Environmental Management in<br>Development|Michael E. Colby|November 1989|C. Evangelista<br>32645|
|WPS314|Primary Commodity Prices and<br>Macroeconomic Variables: A Long-<br>run Relationship|Theodosios Palaskas<br>Panos Varangis|November 1989|D. Gustafson<br>33714|
|WPS315|Notes on Patents, Distortions,<br>and Development|Julio Nogu6s|||
|WPS316|TheMacroeconomics of Populism<br>in Latin America|Rudiger Dornbusch<br>Sebastian Edwards|December 1989|R. Luz<br>615e8|
|WPS317|Price and Quality Competitiveness<br>of Socialist Countries' Exports|Zdenek Drabek<br>Andrzej Olechowski|December 1989|Z. Drabek<br>72162|
|WPS318|Sovereign Debt Buybacks as a<br>Signal of Creditworthiness|Sankarshan<br>Acharya<br>Ishac Diwan|December 1989|S. King-Watson<br>33730|
|WPS319|Trends in South-South Trade and<br>the Potential in Non-Discriminatory<br>Liberalization of Barriers|Refik Erzan<br>|December 1989|G. Ilogon<br>33732|
|WPS320|Protection Facing Exports from<br>Sub-Saharan Africa in the EEC,<br>Japan, and the United States|Refik Erzan<br>Peter Svedberg|November 1989|G. Ilogon<br>33732|
|WPS321|Economic and Policy Determinants<br>of Plublic Sector Deficits|Jorge Marshall<br>Klaus Schmnidt-Hebbe|December 1389<br>l|S. Jonnakuty<br>61769|
|WPS322|Earmarking Government<br>Revenues: Does It Work?|William McCleary|December 1989|A. Bhalla<br>60359|
employment is defined as employment not covered by social security. Informal employment may or may not be voluntary but a recent literature on developing countries found that in countries such as Argentina, Brazil and Mexico informal employment is mostly of a voluntary nature (Bosch and Maloney, 2010).

Transitions between formal and informal employment are very consistent across the four groups considered. Transitions from inactivity to informal work are the largest for all groups and all years with the exception of urban males. For this group, the most important transitions are from unemployment to informal and viceversa. Therefore, transitions into informality from other sectors are much larger than transitions into formality.

The most mobile of the groups are urban men and rural females with over 20% of people in these groups changing status every year. As previously observed, upwards mobility dominates but mobility seems to decline over time for all groups. Also positive is the fact that flows that involve formality have tended to increase for both men and women while flows that involve informality seem to have decreased for men.

**Table 8 –Transition across Formal and Informal Employment (% of total transitions)**

|||M|ale|Ur|ban|Fe|male|||M|ale|Ru|ral|Fe|male||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||07/0<br>8|08/0<br>9|09/1<br>0|10/1<br>1|07/0<br>8|08/0<br>9|09/1<br>0|10/1<br>1|07/0<br>8|08/0<br>9|09/1<br>0|10/1<br>1|07/0<br>8|08/0<br>9|09/1<br>0|10/1<br>1|
|F-->I|11|12|12|12|5|5|6|6|9|6|8|8|0|1|1|1|
|F-->In|3|3|3|4|5|5|6|6|0|0|1|1|0|0|0|0|
|F-->Un|1|2|2|2|1|2|1|1|0|1|0|0||0|0||
|I-->F|13|14|14|16|7|7|7|5|8|10|10|9|1|1|1|1|
|I-->In|10|11|11|9|20|21|19|20|21|20|20|22|46|45|42|43|
|I-->Un|14|13|13|12|4|4|5|4|13|12|11|12|0|1|1|1|
|In-->F|2|2|2|2|4|5|6|5|0|1|1|0|1|0|1|1|
|In-->I|12|12|11|11|24|22|21|23|24|26|24|23|48|49|51|50|
|In-->Un|8|7|8|7|13|12|12|13|5|5|5|5|1|1|2|2|
|Un-->F|2|2|2|2|2|1|2|1|1|0|1|1|0|||0|
|Un-->I|19|19|17|19|5|5|5|5|16|17|19|18|1|1|1|1|
|Un-->In|5|5|5|4|11|11|11|11|1|2|2|2|1|1|1|1|
|_Upward_<br>|_56_|_55_|_54_|_57_|_54_|_53_|_53_|_51_|_54_|_58_|_58_|_55_|_52_|_52_|_55_|_54_|
|_Total (% of_<br>_pop.)_|_21_|_20_|_20_|_20_|_14_|_13_|_12_|_12_|_15_|_14_|_14_|_13_|_25_|_22_|_22_|_21_|

Source: Authors’ estimations from LFSs 2007-2011. F=Formal; I=Informal

# **5. Summary and discussion**

During the past twenty years Morocco has implemented a wide range of economic and social reforms that have delivered in terms of growth and population welfare. More recently, the country has been able to deliver on these two dimensions during a volatile period characterized by a major global shock and sharp variations in agricultural production. Yet, these positive developments are not reflected by the main labor market indicators as it has been observed elsewhere in developed and developing economies alike. This paper investigated the question of whether - behind these labor market aggregates – we could find positive 18