rafmacalaba/datause-encoder-data huggingface dataset:
countries. Both measures of short-term debt are higher among corporations in weaker minority rights countries and again the difference is statistically significant. Finally, profitability appears to be significantly lower among corporations in weaker minority rights countries.

Breaking down results by the specific minority rights index-values, we do not find many monotonic relationships. For some variables, we find a U-shaped, for other an inverse U-shaped pattern, and for some no pattem at all. For profitability measures, for example, we find that profitability generally increases with the protection of equity rights, however, for the index value of 3, profitability is less than for equity rights values of 2 and 4. We expect that firm-specific characteristics play a role in explaining this particular effect, but also venture that the relationship between firm financing patterns and minority rights is complex.

We next use the Demirguc-Kunt and Levine (1999) classification of countries into bank-oriented and market-oriented systems to explore the relationship of the type of financial system with firm risk and profitability characteristics (Table 7). We find that corporations in bank-oriented systems have more risky financial structures and appear less profitable. These corporations have statistically significant higher cash-flow variability and higher financial leverage. Operating leverage and liquidity measures do not differ significantly. Interest coverage is significantly lower for corporations in bankcentered countries. Corporations in those countries also use significantly more short-term debt than their counterparts in market-based economies. Finally, firms in market-based financial systems have statistically higher profitability.

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the _gram sabha_ , which has been a broadly effective forum for local governance.

Te notion that outside intervention might have unintended consequences on local dynamics of citizen participation is not new. For example, Bano (2012) studies the consequences of externally funded NGOs and Pakistan, and finds that these organizations ofen displace organic community-based groups and upset informal processes by which could monitor one another. In Kenya, Gugerty and Kremer (2008) evaluate the impact of a funding program to strengthening women’s associations and find that the introduction of external funds has litle impact on the groups’ activities, but leads to a substantial change in the membership of groups, encouraging the entry of younger, more educated women. In our study, the consequences of external intervention have less to do with membership, but we do see that the introduction of this external program may meaningfully shif conversation about relevant governance issues.

Of course, the growth of project-specific conversation may be a consequence of PVP’s unique design, which specifically encourages women to publicly administer the program’s activities within the village. Tis feature of PVP is just one of the many channels by which this intervention may boost women’s civic engagement; other channels include the provision of credit access, livelihoods training, and social networks fostered by the group-based format of the program. Evidence from an earlier economic evalution of PVP by Khanna et al. (2015) suggests that all of these mechanisms may be at play; in their household survey, they find that PVP reduces the high cost debt burden of target households, improves women’s intrahousehold decision-making power, and boosts their willigness to engage with public officials. Teoretically, each of these components may _individually_ raise women’s ability to participate in the public sphere: With greater access to credit and livelihoods, women may have more decision-making power and autonomy within the home — power which earns them more public freedoms. Te social networks developed by the group-based format of the program may facilitate collective action (Sanyal, 2014). And the particular focus on women-led administration of PVP may “mechanically” boost the participation of women in the _gram sabha_ , as they use this public space to announce programs and publicize PVP’s activities. Unfortunately, while the bundled nature of this intervention precludes us from 26
How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19?<sup>1</sup> Gi Khan Ten, Josh Merfeld, Kibrom Tafere Hirfrfot, David Newhouse, Utz Pape

**JEL:** C82, E01, I31

**Keywords:** COVID-19, GDP impact estimation, big data

> 1 The team would like to thank the Korea Trust Fund for Economic and Peace-Building Transitions (KTF) for providing funding. The KTF, supported by the Ministry of Economy and Finance, Republic of Korea, is a global fund administered by the World Bank to finance critical development operations and analysis in situations of fragility, conflict, and violence.
# The Impact of Infrastructure on Development Outcomes: A Meta-Analysis<sup>∗</sup>

Vivien Foster Nisan Gorgulu Dhruv Jain Stéphane Straub Maria Vagliasindi Originally published in the Policy Research Working Paper Series on _March 2023._ This version is updated on _June 2024._ To obtain the originally published version, please email prwp@worldbank.org.

**Keywords:** Infrastructure, Transport, Energy, ICT, Meta-analysis.

> ∗Foster: Imperial College London, Gorgulu and Vagliasindi: World Bank. Straub: World Bank and Toulouse School of Economics. Jain: Toulouse School of Economics. We thank Sylvain Chabé-Ferret for insightful suggestions, and Pedro Bom and David Tuesta for sharing their data. Corresponding author: Stéphane Straub, sstraub@worldbank.org.
**Table 4: Relationship between Nighttime Light Luminosity and Sectoral GVA and GDP**

||**Mining** **Co**<br>D|**nstruction**<br>**M**<br>ep. Var: % Annu|**anufacturing**<br>**A: Province Fix**<br>al Change in Me|**Services**<br><br>**ed Effects**<br>asure of Econ|**Agriculture**<br>omic Activit|**GDP**<br>y|
|---|---|---|---|---|---|---|
|% Ch. NTL|0.08***|0.35***|0.15***|0.03***|-0.01|0.08***|
||[5.05]|[8.35]|[6.35]|[7.82]|[-0.37]|[7.55]|
|Constant|0.06***|0.02***|0.05***|0.05***|0.03***|0.04***|
||[58.85]|[7.80]|[33.76]|[175.27]|[19.18]|[62.57]|
|Obs.|798|798|798|798|798|798|
|R-squared|0.02|0.09|0.05|0.03|0.00|0.08|
|**B: Province a**|**nd Year Fixed**|**Effects**|||||
||De|p. Var: % Annua|l Change in Mea|sure of Econo|mic Activity||
|% Ch. NTL|-0.02|0.10**|0.05**|0.00|0.02|0.02*|
||[-1.28]|[2.48]|[2.26]|[0.52]|[0.54]|[1.90]|
|Constant|0.09***|0.13***|0.12***|0.08***|0.08***|0.09***|
||[12.33]|[10.83]|[13.97]|[31.97]|[4.38]|[18.68]|
|Obs.|798|798|798|798|798|798|
|R-squared|0.18|0.61|0.35|0.55|0.10|0.48|
||**C: **<br>De|**Province and Ye**<br>p. Var: % Annu|**ar Fixed Effects:**<br>al Change in Me|**NTL from U**<br>asure of Econ|**rban District**<br>omic Activity|**s**<br>|
|% Ch. NTL|-0.03|0.13**|0.07***|-0.00|0.01|0.02|
||[-1.10]|[2.63]|[2.76]|[-0.44]|[0.30]|[1.51]|
|Constant|0.09***|0.13***|0.12***|0.08***|0.08***|0.09***|
||[12.95]|[10.78]|[13.48]|[31.07]|[4.52]|[18.52]|
|Obs.|798|798|798|798|798|798|
|R-squared|0.18|0.61|0.35|0.55|0.10|0.48|
||**D: Pro**<br>De|**vince and Year**<br>p. Var: % Annu|**Fixed Effects: NT**<br>al Change in Me|**L from Urba**<br>asure of Econ|**n Core Grid**<br>omic Activity|**Cells**<br>|
|% Ch. NTL|-0.06|0.26***|0.11|-0.01|-0.11|-0.00|
||[-1.02]|[2.82]|[1.57]|[-0.65]|[-1.39]|[-0.10]|
|Constant|0.09***|0.14***|0.12***|0.08***|0.07***|0.08***|
||[10.55]|[10.40]|[10.91]|[24.29]|[4.16]|[17.43]|
|Obs.|798|798|798|798|798|798|
|R-squared|0.18|0.61|0.35|0.56|0.10|0.48|

Notes: Robust t-statistics in brackets. *** p<0.01, ** p<0.05, * p<0.1. All regressions use province fixed effects and report t-stats consistent with robust standard errors clustered by province. All regressions analyze 57 urban provinces. A province is defined to be urban if it contains any part of an urban agglomeration. Panel C uses data exclusively from urban districts in a province, which are defined to be districts that contain any part of an urban agglomeration. Panel D uses data from grid cells that were categorized by the GHLS in 2000 to be urban.

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least for � ranging from 0 to 0.5 and for any m). Note that, we have w�(0; 0) = w[11+���n�nRwa] = �<sup>FB</sup> ss<sup>.</sup> Decentralizing the second best solution requires a subsidy rate equal to: such that the subsidy rate is a decreasing function of both � and m: It should be noted that �<sup>SB</sup> ss<sup>can be negative for high emigration rates (when �(�; m) <</sup> 1 + m<sup><u>(w�</u></sup> w<sup>�w)</sup> ). The budget constraint requires �<sup>y</sup> ss<sup>= �SB</sup> ss<sup>eSB</sup> ss<sup>=(1 ��).</sup>

# 6.3 Human capital regressions - Robustness check

The incentive e¤ect of skilled emigration on human capital accumulation remains positive and signi...cant whatever the measures of brain drain used. Table A reports replications of the speci...cations OLS2 and IV2 of Table 1 distinguishing di¤erent ages of entry. We only report estimates for the three main explanatory variables although results for other controls and diagnostic tests are almost identical to those in Table 1. Clearly, Table A supports the robustness of the incentive mechanism and the positive e¤ect of public education subsidies.

In previous version of the paper, we investigated the robustness of this mechanism using functional forms other than the log-linear speci...cation we have adopted here. The incentive mechanism depicted in Table 1 is robust to the alternative speci...cations: results with m90 or ln(1 + m90); rather than ln(m90), can be obtained upon request. It could also be argued that further e¢ ciency gains would be obtained by 30
allocational effects of trade reform on income risk, has additionally argued that increased foreign competition following trade reform will increase the elasticity of the goods and the derived labor demand functions. If a higher demand elasticity translates any given shock into larger variations in wages and employment, lower trade barriers may lead to increased individual income risk.<sup>4</sup> On the other hand, it has also been suggested that the world economy is likely to be less volatile than the economy of any single country, which leads to goods prices that are more stable worldwide than in any single autarkic economy. This opens up the possibility that greater openness may reduce the variance in individual incomes. Thus, theoretically, the openness-volatility relationship is ambiguous, that is, the theoretical literature does not offer a strong prior on the sign or magnitude of this relationship.<sup>5</sup> In this paper, we study _empirically_ the effects of trade policy on individual income risk using the following approach. For each industry (sector), we use longitudinal data on individual earnings to estimate time-varying parameters of individual income risk using a methodology that follows the approach taken by the extensive empirical literature on labor market risk.<sup>6</sup> More specifically, we focus on the variance of (unpredictable) changes of individual income as a measure of income risk, and carefully distinguish between transitory and persistent income shocks. The distinction between transitory and persistent income shock is important since workers can effectively “self-insure” against transitory shocks through borrowing or own savings, which implies that the effect of these types of shocks on workers’ consumption and welfare are quite small (Aiyagari (1994), Heaton and Lucas (1996), Levine and Zame (2002)).

> 4While Rodrik (1997) appears to have in mind mostly aggregate volatility, it is easy to see that his arguments equally apply to individual income volatility if there are idiosyncratic shocks to firm-level productivity.

> 5Clearly, this sign-ambiguity does not extend to the short-term re-allocational effect of trade policy reforms which, as we have discussed above, are generally expected to raise income risk. However, we do not have strong priors on the magnitude of this relationship either.

> 6See, for example, Carroll and Samwick (1997), Gottschalk and Moffitt (1994), Gourinchas and Parker, (2002), Hubbard, Skinner, and Zeldes (1994), Meghir and Pistaferri (2004), and Storesletten, Telmer, and Yaron (2004).

2
_s - nfiae - c_ _dCb-==-(r'nfa'e+recprc,-a)+ cp_ (16) These definitions of the central bank's real deficit<sup>reveal clearly the transfers of</sup> real resources that may take place in an inflationary<sup>economy. They also indicate what</sup> type of corrections may be needed in order to<sup>stabilize an economy where the monetary</sup> imbalances are rooted in the central bank. If the<sup>seignorage collected by the central bank</sup> is being channelled towards the servicing of foreign<sup>liabilities and the concession of</sup> credit subsidies to the public and private sectors,<sup>monetary control may require a variety</sup> of measures, such as the increase in interest rates<sup>on central bank credits, the interruption</sup> of central bank's explici **t** ransfers to the government's budget, and possibly the absorption of central bank foreign liabilities by the government.<sup>This last measure is</sup> required if the real stock of central bank credits has fallen<sup>to such low levels that an</sup> increase in real interest rates to reasonable levels<sup>does not generate enough real resources</sup> to cover the servicing of foreign liabilities.

For instance, the Yugoslav stabilization program of<sup>1990 included the transfer to</sup> the federal budget of central bank credit subsidies<sup>to agriculture and exports, as well as</sup> the absorption of most of the central bank's foreign liabilities<sup>by the federation. Such</sup> absorption took place through the replacement of the large<sup>stock of foreign exchange</sup> losses in the central bank by an equivalent stock of federal<sup>government bonds indexed to</sup> the exchange rate and yielding an interest rate equal to LIBOR.<sup>Of course, all these</sup> 4 . measures required ultimately a fiscal adjustment by<sup>the federal government'</sup> 1<sup>4</sup> See Coricelli and Rocha (1991) for an analysis of the<sup>Yugoslav and Polish stabilization</sup> programs of 1990 and Bole and Gaspari (1990), Mates<sup>(1991), Rocha (1991), and The</sup> World Bank (1989) for detailed studies of Yugoslavia's quasi-fiscal deficits and inflation.

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- 13 -

more gas than those far distant from such reserves (e.g. Iceland or Portugal).

- (Li) the industrial mix plays an important role in determining fuel share as shown below. If different industries tend to favor different fuels then the pattern of industrial specializatlon<sup>will</sup> be important ln explaLnLng the fuel shares in the total industrlal uector. since the LndustrLal pattern responds to many other factors than the relative price of dlfferent fuels, it is unlLkely that lt would be posslble, by changLng the<sup>attractiveness of</sup> dLfferent fuels, to achLeve the range of varlatlons ln fuel use lllustrated across the range of O.B.C.D. countries. It is possible to glve equivalent figures for an earlier date,<sup>but glven</sup> the large changes ln industrial structure that have taken place over the last twenty years in many countrLes this is left to<sup>the</sup> more disaggregated analysi below.

fuel Shares in Electriclty por Individual O.B.C.D. Countries The use of primary fuels for power generation (valued in<sup>NTOE) is</sup> avallable over a long perlod of tLme for all the O.B.C.D. countrles.<sup>Slnce power</sup> generatLon is a sLngle lndustry there ls no problem of changing shares of<sup>output</sup> to contend with as for the total LidustrLal sector. Table 2.6 gives<sup>shares for</sup> 1970 and table 2.7 shares for 1988.

Table 2.6S hares of Primary Fuels in Power Generation for O.E.C.D. Countries ln 1971

|Coal andOther<br>SolLd<br>Fuels|Oil|Gas|Nuclear|Hydro|
|---|---|---|---|---|
|Australia<br>75.60<br>Austria<br>9.56<br>Belgium<br>33.64<br>Canada<br>17.91<br>|4.62<br>6.91<br>52.08<br>3.06<br>|0.86<br>12.21<br>13.29<br>3.04<br>|0.00<br>0.00<br>0.19<br>0.49<br>|18.39<br>70.72<br>0.81<br>75.49<br>|
|Denmark<br>31.21<br>Finland<br>20.20<br>France<br>30.22<br>Germany<br>68.62<br>Greece<br>38.32<br>Iceland<br>0.00<br>Ireland<br>1.24<br>Italy<br>4.8<br>Japan<br>16.72<br>Luxembourg<br>47.21<br>Netherlands<br>19.81<br>New Zealand<br>6.12|68.67<br>27.55<br>21.97<br>15.00<br>34.84<br>2.96<br>53.79<br>48.80<br>58.47<br>11.41<br>32.60<br>3.31|0.00<br>0.00<br>4.50<br>5.53<br>0.00<br>0,00<br>0.00<br>4.85<br>1.25<br>0.09<br>46.69<br>0.06<br>|0.00<br>0.00<br>3.89<br>2.49<br>0.00<br>0.00<br>0.00<br>2.70<br>1.28<br>0.00<br>0.90<br>0.00<br>|0.12<br>42.10<br>38.94<br>7.32<br>26.84<br>97.04<br>13.85<br>37.49<br>22.28<br>41.29<br>0.00<br>90.51<br>|
|Norway<br>0.00<br>Portugal<br>4.90<br>Spain<br>21.65<br> <br>|0.63<br>14.44<br>27.14<br>|0.00<br>0.00<br>0.01<br>|0.00<br>0.00<br>1.63<br>|99.37<br>78.18<br>49.49<br>|
|Sweden<br>0.28<br>|30.92<br>|0.00<br>|0.09<br>|68.49<br>|
|switzerland<br>0.00|5.92|0.00|4.98|89.10|
|Turkey<br>34.55<br>|30.30<br>|0.00<br>|0.00<br>|35.15<br>|
|United Kingdom 68.48|18.48|0.33<br>|10.44<br>|2.27<br>|
|U.S.A.<br>46.39|12.12|24.58|1.44|15.46|
|O.E.C.D.<br>38.70|19.90|14.10|2.90|24.20|

Sggrces A for table 2.1.
MALI’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE 70 percent and 30 percent of the market share, respectively. At close to 60 percent, Mali’s mobile market has the highest Herfindahl-Hirschmann index in West Africa (figure 22).

**Figure 22. The mobile market in Mali is highly concentrated**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>2005 2008<br>Herfindahl-Hirschmann Index<br>Mali Niger Cameroun Ghana Burkina Faso Benin Nigeria<br><!-- End of picture text --> Source: World Bank (2009a) Note: Herfindahl-Hirschmann index (HHI) is a commonly accepted measure of market concentration. It is calculated by squaring the market share of each firm competing in the market and then summing the resulting numbers. A HHI of 100 indicates the market is a monopoly, while a lower the HHI the more diluted is the market power as exerted by one company/agent.

The second challenge is related to the Internet market. Over the last seven years, Internet penetration has increased substantially, and prices have dropped. In 2000, use of the Internet was almost nonexistent; by 2007, penetration had risen to 6 percent. The increase in access coincided with an increase in service quality. In 2000, connection speeds were very slow at less than 1 Mbps. In 2007, after Sotelma and Orange Mali had connected to SAT-3, connection speeds had reached 17 Mbps per person. Still, Mali lags behind other West African countries in both internet penetration and international internet bandwidth (figure 23).

In terms of the internet market, the institutional framework of Mali’s ICT sector, which allowed for the expansion of mobile markets, is now becoming a major deterrence for the expansion of Internet. A good illustration of the legal gap is the regulatory vulnerability of Internet Service Providers (ISPs). After reaching 20 active ISPs in 2008, Mali now has only 5 ISPs, two of which are wholesalers of bandwidth. The two largest operators make access difficult engaging in predatory and discriminatory practices against small ISPS, overcharge for bandwidth, and bundle their service in such a way that the market is unattainable for new and small ISPs.

39
closures for smaller exporters—so the seemingly pro-equity regulations in labor reduce equity for certain subsets of the population.

Stringent labor regulations have allocation consequences in high-income developing countries as well. Scoring the highest in an index of strictness of employment law (Botero et al. 2004), Brazil is one of the most regulated countries regarding labor in the world. Not surprisingly, in 1999, 40 percent of the private sector was informal. Almeida (2005) investigates how regional differences in labor regulation enforcement affect informality and firm labor productivity. Labor regulation is measured as the number of fines related to labor issued in each region. She finds that a stricter enforcement of labor regulation leads to less informality but lower productivity and investment. The results are robust when the labor regulation proxy is instrumented by measures of access of labor inspectors to firms, and measures of general law enforcement in the area where the firm is located. Using the same data, Almeida and Carneiro (2009) find that a strict enforcement of labor regulations constrains firm size and leads to higher unemployment. Recognizing that the enforcement of labor regulation may be endogenous, the authors instrument it with the distance between the city where the firm is located and surrounding enforcement offices while controlling for a rich set of city characteristics.

A channel through which labor regulations worsen efficiency is by increasing the discrepancy between labor costs and labor productivity and by increasing the range of productivity across firms (Petrin and Sivadasan 2006). Proxying job security regulations by the costs of dismissing employees, they investigate the effects of two changes in Chile. In 1984, the government no longer exempted firms that could show “economic cause” for dismissal from severance pay. In 1991, the government increased the ceiling of severance pay from 5 to 11 months and added a 20 percent surcharge if the employer could not prove economic cause. Petrin and Sivadasan measure the welfare effects by measuring the mean and the variance of the difference between the marginal revenue product and the marginal input prices using Chilean manufacturing data from 1979 to 1996. They find a substantial increase in both the mean and the variance of within-firm gaps in response to increasing firing costs. The timings in increasing gaps and in the regulatory changes are consistent. In contrast, the gaps do not increase for inputs that are not directly affected by firing costs.

Another channel through which stringent labor regulations hurt efficiency is by slowing down the creative destruction process. Haltiwanger et al. (2008) study how labor regulations affect job turnover by using a rich new harmonized firm-level data on job flows across industries and size classes for 16 industrial and emerging economies over the past decade. They examine whether regulations at the country level affect more regulation-vulnerable industries to a greater extent.

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