rafmacalaba/data-use-mentions-extended huggingface dataset:
|21|
|19|Investment from China rising; investment from UK and US falling<br>KenInvest 2015||
|20|China and France top sources of FDI infows for Kenya (2012)<br>UNCTAD FDI/TNC database 2015<br>. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|22|
|21|China and UK hold the most FDI stock in Kenya (2012)<br>UNCTAD FDI/TNC database 2015<br>. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|23|
|22|Kenya’s mobile telephone subscriptions grew quickly over last decade<br>International Telecommunications Union 2016||
|23|China invests most in metals and communications in Kenya (2003-2015)<br>fDi Intelligence from The Financial Times Ltd 2015<br>. . . . . . . . . . . . . . . . . . . . . .|25|
|24|Chinese companies invest most in manufacturing (2003-2015)<br>fDi Intelligence from The Financial Times Ltd 2015<br>. . . . . . . . . . . . . . . . . . . . . .|25|
|25|Chinese investment per project highest in headquarters creation and manufacturing<br>(2003-2015)||
||fDi Intelligence from The Financial Times Ltd 2015<br>. . . . . . . . . . . . . . . . . . . . . .|26|
|26|Chinese companies create most jobs in the communications sector (2003-2015)<br>fDi Intelligence from The Financial Times Ltd 2015<br>. . . . . . . . . . . . . . . . . . . . . .
one exception to this trend; it provides guidance on potential solutions to the typical problems of lagging regions, namely access to finance; low productivity and educational attainment; weak innovation systems and institutional quality; high emigration; and low public and private investment.<sup>9</sup> However, it does not yet bring evidence on whether lagging regions have realistically addressed these constraints, and if doing so has led to growth. Evaluations of typical interventions (e.g. access to finance,

> 5 Author’s elaboration on Eurostat data.

> 6 The total budget for ERDF during the period 2021-2027 is estimated at €201 billion, and Cohesion Policy funds will be €331 billion – a smaller total budget owing to the departure of the United Kingdom. For details, see the report “Regional Development and Cohesion Policy beyond 2020: The new framework at a glance”, available at “https://ec.europa.eu/regional_policy/en/2021_2027/”.

> 7 Other instruments such as Community-Led Local Development (CLLD) may also be used. CLLDs tend to focus on a smaller scale than ITIs, and are implemented by a Local Action Group (LAG) which may be constituted by several smaller municipalities. For a review of ITIs and CLLDs, see van der Zwet et al. (2014).

> 8 Data from Joint Research Council STRAT-Board, accessed on May 26, 2020 and available at “https://urban.jrc.ec.europa.eu/stratboard/”. Some examples are the integrated plans for Larnaca, Limassol, Paphos, and other cities in Cyprus; city strategies for Aalborg, Odense, and other Danish cities; and city contracts in France for Coeur de France town, Vierzon, Amboise, and others; and integrated city programs in Italy for Aversa, Caserta, Salerno, and several others.

> 9 Similar conclusions are reached also by Farole et al. (2018).

3
This is defining cities as locations with more than 500,000 inhabitants. There are a further 21 respondents who moved to areas that, while administratively recognized within Tanzania as cities, have a population below 500,000 (Arusha, Tanga and Mbeya). Results do not change if we change the definition from a population-based one to an administrative one.<sup>12</sup> The occupational and spatial data are

> 10 De Weerdt et al (2012) provide more details.

> 11 Farming includes both agriculture and livestock keeping and can be both in self-employment or working for others (typically as a casual labourer).

> 12 For Tanzania we use population projections per district based on the 2002 census data (URT, 2006b), which are available at the district level. These include the population living in the ‘green belts’ around the cities in question. Administratively Tanzania has the following cities (2002 population in brackets): Mbeya (358,939),

9
In their paper on the determinants of financial system and stock market development, Beck, Demirguc-Kunt, and Levine (2003) also discuss property rights protection. Our methodology and findings differ from theirs in several respects. First, while we use firm-level data on property rights protection, they use a country-level index, compiled by the Heritage Foundation from several private and public sources, and cannot address the issue of whether firm characteristics affect property rights protection. Second, while we consider each institutional theory separately and treat all of them equally, Beck et al (2003) focus on legal origin and settler mortality and use the proxies for other theories simply as control variables. Finally, their sample of 70 countries does not include any of the former Socialist countries that are in our sample. These factors are likely to explain why we find a clear difference in the explanatory power of the legal origin and endowment views for property rights protection and for several related variables, and their paper does not.

The rest of the paper is organized as follows: Section 2 discusses the various institutional determinants of property rights that we investigate in this paper. Section 3 presents the empirical methodology. Section 4 presents the data and the results of the variance decomposition analysis. Section 5 presents additional robustness tests and we conclude with suggestions for future research in section 6.

# **2. Institutional Determinants of Property Rights Protection**

In order to understand better the determinants of firm’s perceptions of property rights protection, we present a one-to-one comparison of four different institutional theories that have been shown by current literature as being important predictors of property rights - Legal Origin, Endowments, Culture and Ethnic Fractionalization.

LLSV (1998) argue that legal systems differ in how much they protect the rights of private investors vis-à-vis the state and minority shareholders. They argue that legal systems that evolved from common law traditions have tended to be supportive of private property rights. By contrast, civil law systems were established by states as acts of policy. They tend to be designed
> 24 Baird and Özler (2012) suggest that self-reported enrollment is often overstated and recommend collecting schoollevel administrative enrollment data. In our survey, when comparing parental self-reports and school administrative data, we find that 11.4 percent of all children reported by their parents to be enrolled are not enrolled according to the school data. Appendix Table 1 provides a qualitative summary of the main enrollment results using the parental reports and school-level administrative data. As discussed below, results are consistent with both data sources. Appendix Table 2 presents results using the parental self-reports. Appendix Table 3 includes the other empirical specifications for the school-based data for all the sub-categories analyzed in Table 5 with consistent results.

19
average consumption in China has had an equalizing effect on EAP-wide inequality, while the accompanying increase in inequality in China had the opposite effect. Specifically, China’s within-component increased from 0.13 to 0.22, while its between component declined from 0.14 to -0.04. Therefore, China’s contribution to total GE(0) inequality actually declined (from 0.26 to 0.18, or from 104% to 58% of total regional inequality), which is entirely driven by its growth in the mean. This equalizing effect from China was more than counteracted by the other countries, resulting in an increasing GE(0) overall.

These results, specifically on the direction of regional inequality as well as its country decomposition, are robust to a number of methodological checks. In the Appendix, we explain and estimate four robustness checks – (1) within-country price differences for a larger set of countries, (2) 2005 PPPs, (3) a balanced sample of countries, and (4) the raw data without a parametric Lorenz curve.

> 17 As explained in Jirasavetakul and Lakner (2016), this comparison of the between-country contribution is robust to using the method introduced by Elbers et al. (2008), which is particularly useful in settings where the number of groups and their relative sizes vary across comparators.

> 18 Of course, this does not imply that average consumption of Other East Asia has actually fallen. However, as Table 2, Panel H, shows, average consumption in Other East Asia has grown slower than the EAP-wide average – growth of 43%, compared with 265% for EAP.

10
areas, the sample under-represents the agricultural sector, which represents a significant fraction of employment in the developing world.

Our analysis is based on the ISCO-08 occupational classification at the 1-digit level. We do not use a higher level of disaggregation for two reasons. First, because for most of the countries covered in STEP surveys, the sample size is not large enough to make reliable inferences using more detailed occupations, as many of the cells would contain very few observations or be empty. Second, since the second goal of this paper is to make comparisons across countries and across time, it is not feasible to harmonize the occupational classifications for all the household surveys (which are around 600 in this study). This is because in addition to changes in the ISCO over time, many countries use their own-specific occupational categories that are difficult to map to ISCO at finer disaggregation levels. Appendix 3 shows that while the level of aggregation may affect the 9
# **ABSTRACT**

This paper estimates the degree of misalignment of the CFA franc since the introduction of the euro in 1999. Using a relative purchasing power parity-based methodology, the study develops a monthly panel time series dataset for both the Central African CEMAC zone and the West African UEMOA zone to compute a trade-weighted real effective exchange rate (REER) indexed series from January 1999 to December 2004. The main finding of the paper is that the REER appreciated by close to 8 percent in UEMOA and 7 percent in CEMAC, influenced by the volatility in the euro-dollar bilateral exchange rate and conservative monetary policies in the two zones, resulting in a partial loss of competitiveness in export markets. The lower appreciation in Central Africa can be explained by lower inflation in CEMAC than in UEMOA and by the greater trade with higher inflation East Asian countries, partially offset by the peg to the dollar. However, the inclusion of “unrecorded trade” results in an appreciation of only 6 percent in the UEMOA zone and 6 percent in the CEMAC zone due to higher inflation in the two countries with unmonitored cross-border flows, Ghana and Nigeria. Using time series econometrics, an EngleGranger two stage procedure for cointegration, and an error correction framework, a single equation modeling of the real exchange rate from 1970 to 2005 as a function of terms of trade, economic openness, aid inflows, and a dummy representing the 1994 devaluation finds little statistical evidence of a long-run equilibrium exchange rate that is a vector of economic fundamentals. The dummy explains most of the real exchange rate behavior in the two zones, while openness in UEMOA has contributed to an appreciation of the REER.

3
trends going forward, as there is a risk that children, who regressed in learning during COVID-19, may struggle with the new curriculum and drop out in the months or years that follow.

These sharp fluctuations also imply that routine data collections are necessary during the pandemic to monitor the situations on the ground. However, even high-frequency phone surveys, which collect household-level information on children’s school attendance, only provide a very partial picture as there can be significant intra-household variability. The data used in this paper were pre-selected for the availability of individual-level data on school attendance. In what follows, we turn to gender differences as one important dimension of intra-household variation.

**Table 1: School attendance of adolescents before and during the pandemic, by country and survey round**

|**Country**|**Period (survey)**|**% of children aged**<br>**10-18**<br>**attending**<br>**school***|**% of children aged**<br>**10-18**<br>**attending**<br>**school inperson**|**School status**|
|---|---|---|---|---|
|Burkina Faso|||||
||2018-19(LSMS)|59.9||Pre-COVID|
||Dec. 2020(HFPS R5)|71.6|71.6|Fullyopen**|
|Ethiopia|||||
||2018-9(LSMS)|72.4||Pre-COVID|
||Dec. 2020(HFPS R8)|77.6|51.8|Partiallyopen|
||April-May2021(HFPS R11)|78.4|76.7|Fullyopen|
|Kenya|||||
||2015-16(KIHBS)|91.8||Pre-COVID|
|
Survey of Bank Regulation and Supervision.<sup>16</sup> Table 1, Panel B reports basic summary statistics for the firm survey variables and country-level variables. More than half of the firms in our sample have access to finance; in other words, they use at least one of three credit products such as loans, lines of credit, or

> 12 The Herfindahl index, calculated as gives a greater weight to larger banks. 13 At the firm-level, we have over 68,000 observations.

> 14 Because we use one year lagged values of the Lerner index in our regression, we report bank data for years 20012009.

> 15 Data available at www.doingbusiness.org

> 16 Data available at http://go.worldbank.org/SNUSW978P0

7
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predicted. As for price cost margins, they have no significant effects on either the short run or the long run elasticity.

For white collar workers, no tariff variable has any impact on the own wage elasticities although the exchange rate has the opposite of the predicted effect through the lagged own wage. No trade flow variable has any impact, but the real exchange rate does have the predicted effect here through reducing the coefficient on lagged employment. Further, non-trade barriers do decrease long run elasticities through the coefficient on lagged employment. Increased prices cost margins appear to increase the own wage elasticity.

# **Conclusions**

This paper has argued that the case that trade liberalization should increase own wage elasticities, while compelling in the case of competitive import competing industries, is perhaps less so in the frequent case of imperfectly competitive, non-tradeable, or even export industries. It has then tested the hypothesis using establishment level panel data from three countries with periods of liberalization.

The results show that estimates of elasticities do change greatly in magnitude, if not significantly so, across time and that comparisons across countries should take this into account when attempting to make inference about the flexibility or efficiency of labor markets. But more importantly, the data provide only very mixed support for the idea that trade liberalization has an impact on own wage elasticities and no consistent patterns emerge. If globalization is making the lives of workers more insecure, it is probably working through some other mechanism than that examined here.

23
Second, we need a measure of potential (per-capita) child income, _yc_ . However, we do not observe potential incomes for those children in school. We therefore predict child income (for all children) using earnings data from children reporting earning an income. One may be concerned with selection bias in such a procedure; however, as shown in Attanasio et al (2011), there is no evidence of selection effects on children’s earnings, likely due to the fact that the jobs children perform in these rural villages are very lowskilled. Thus, our predicted measure of potential child income, _yc_ , is simply a function of child age, child gender, and area characteristics (see Appendix B.3 for details on how we estimate potential child incomes).

Using data from our sample of eligible, treated 12-15 year-old children for the years 1998 and 1999, and using our estimate of E � _PI_ � from Table VII above, we solve Equation (14) for _γ_ . Our results are presented in Table VIII below. Our curvature estimate is _γ_ = 1 _._ 05. Interestingly, this estimate is very similar to that estimated in Chetty (2006) who finds a value of _γ ≈_ 1, i.e., _u_ ( _c_ ) = _log_ ( _c_ ) (similarly, Layard and Mayraz (2008) find _γ_ = 1 _._ 26). When we vary mothers’ earnings from 0% to 100% as much as fathers’ earnings, we find that _γ_ ranges from [0 _._ 72 _,_ 1 _._ 13].<sup>32</sup> If we instead assume mother’s income is equal to 80% of the mean value of father’s income, we find _γ_ = 1 _._ 15.

TABLE VIII: Curvature of Utility

|E<br>�_I_<br>_P_<br>�|0.21|
|---|--
facilitate the entrance of mothers into the labor market.

We also propose different measures of social norms and attitudes towards women in the society using data from 2018 Latinobarómetro. The first captures the share of males considering that a team of women and men will have better results than a team of only men. The second captures the opinions towards women and men being equally skilled in science and technology. Results reported in column (4) of Table 2 show a that the positive association holds (but its non-significant with the second measure).

Finally, column (5) of Table 2 reports the main findings when the sample is restricted to urban areas. The direction of the main findings remains the same. However, the penalty associated to young children is larger than in the baseline estimates. In urban areas, women having an additional child in the 0-3 age range are 6 percentage points less likely to participate in the labor market (the 16
<mark>Source: Fukuyama et al. (2022)</mark> <mark>The data thus enable scholars to understand systematically how sociodemographic factors like gender differences vary systematically across countries – from employee attitudes such as motivation or job satisfaction, to perceptions of male and female employees of management practices such as leadership. Observing these differences, scholars may seek explanations for why, in some countries, men or women respond more favorably than in others. To our knowledge, this research endeavor – exploring variation across countries in the experience of different demographic groups of public servants – was previously not feasible for scholars at scale.</mark> <mark>Finally – and perhaps most straightforwardly – our indicators may also help scholars implementing surveys of public servants in specific countries understand how their case countries are similar or different from others in the world in employee attitudes or management practices. We hope the indicators can thus lead to more empirically grounded case selection and generalizability discussions in country-specific research.</mark>

# **<mark>Relating the Global Survey of Public Servants to Other Governance</mark>**

# **<mark>Indicators</mark>**

<mark>How do existing composite governance indicators relate to the GSPS indicators? To illustrate, consider, first, the relation between GSPS indicators and the widely used Worldwide Governance Indicators (World Bank 2022). We do not intend the comparison to be a `validation’ exercise, but rather an exploration of the linkages between the GSPS data and the existing literature. Figure 11 provides scatterplots showing the relationship at the country-level between three GSPS indicators – work motivation, pay satisfaction and perceived job stability of public servants – and the two indicators from the Worldwide</mark> 21
Shastry, G.K., and D.N. Weil (2003), “How much of Cross-Country Income Variationis Explained by Health?”, _Journal of the European Economic Association_ , April-May 1(23):387-396.

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similar data for 139 economies and 819 harmonized household surveys. They provide comparable estimates because they hold constant the definition of the dependent variable, the set of control variables, the sample definition, and the estimation method for all surveys in the sample. Psacharopoulos and Patrinos (2018) update their decennial review of the literature and review the latest trends and patterns based on 1,120 estimates in 139 countries.

Montenegro and Patrinos (2014) find that there is a decreasing pattern over time, but also that the returns to tertiary education are the highest. Psacharopoulos and Patrinos (2018) find that the private average global return to a year of schooling is 9 percent a year and that the private returns to higher education increased. Both find higher returns for women.

<!-- Start of picture text --> Figure 1: Years of schooling and returns over time<br>9.1<br>8.7<br>8.6<br>7.8<br>Pre 2000 Post 2000<br>Mean years of schooling Rate of return (%)<br><!-- End of picture text --> Source: Psacharopoulos and Patrinos 2018 The rapid expansion in schooling in terms of access, enrollment and total years of schooling is expected to reduce the earnings advantage, everything else being equal, of course. Average years of schooling worldwide were only one year in 1990, rising to 3.2 by 1950, to more than 8.5 by 2010 (Barro and Lee 2015). However, although the average schooling level of the working population increased in the early 2000s, the overall private rate of return to schooling also increased (Figure 1). Before 2000, average years of schooling were 7.8 and the returns to 7