rafmacalaba/datause-encoder-data huggingface dataset:
only in conjunction with policies for local procurement. Moreover, some of the mining-related papers have focused on mining in an African context, exploring a range of outcomes, including HIV-transmission and sexual risk taking (Corno and de Walque 2012; Wilson 2012), women’s empowerment (Benshaul-Tolonen 2018), infant mortality (Benshaul-Tolonen, 2019) and labor market outcomes (Kotsadam and Tolonen 2016). Mining is also associated with more economic activity measured by nightlights (Benshaul-Tolonen, 2019; Mamo et al, 2019).

Kotsadam and Tolonen (2016) use DHS data from Africa, and find that mine openings cause women to shift from agriculture to service production and that women become more likely to work for cash and year-round as opposed to seasonally. Continuing this analysis, BenshaulTolonen (2018) explores the links between mining and female empowerment in eight goldproducing countries in East and West Africa, including Ghana. Women in gold mining communities have more diversified labor markets opportunities, better access to health care, and are less likely to accept domestic violence. In addition, infant mortality rates decrease with up to 50% in mining communities, from very high initial levels (Benshaul-Tolonen, 2019). In a study that focuses exclusively on Ghana, Aragón and Rud (2013) explore the link between pollution from mining and agricultural productivity. The results point toward decreasing agricultural productivity because of environmental pollution and soil degradation, which could have negative welfare effects on households that do not engage in mining activities or in indirectly stimulated sectors. Lower productivity in agriculture could potentially push households to engage in mining-related sectors, in addition to pull factors such as higher wage earnings in the stimulated sectors.

We explore the effects of mining activity on employment, earnings, expenditure, and children’s health outcomes in local communities and in districts with gold mining. We combine the DHS and GLSS with production data for 17 large-scale gold mines in Ghana. We find that a new large-scale gold mine changes economic outcomes, such as access to employment and cash earnings. In addition, it raises local wages and expenditure on housing and energy.

An important welfare indicator in developing countries is infant mortality, and we note a large and significant decrease in mortality rates among young children, at both the local and district levels.<sup>1</sup> We hypothesize that increased access to prenatal care is one of the mechanisms behind the increased survival rate.

> 1 In the 2010 Ghana population census average district size is 112,000

3
**Table A8: Effects of refugee presence on household welfare with analysis at cluster level and the distance weighted refugee index at 100km from the clusters (Panel 2009-2012)**

||Log of|welfare(consumpti|onaggregate perad|ult equivalent)|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Log of refugees (100km)|0.0018|0.0020|0.0170|0.0319**|
||(0.0186)|(0.0185)|(0.0154)|(0.0147)|
|HH head age||0.0025|0.0119**|-0.0004|
|||(0.0051)|(0.0056)|(0.0166)|
|Age squared||-0.0000|-0.0001|-0.0000|
|||(0.0000)|(0.0001)|(0.0001)|
|HH head sex (male)||0.0044|0.0239|-0.0795|
|||(0.0348)|(0.0378)|(0.0634)|
|Household size|||-0.0262***||
||||(0.0054)||
|**_HH head marital status_**|||||
|Married monogamously|||-0.4288**||
||||(0.1652)||
|Married polygamously|||-0.3746**||
||||(0.1728)||
|Separated (divorced/widowed)|||-0.4146**||
||||(0.1729)||
|**_HH head education level_**|||||
|Completed primary sch|||0.2227***||
||||(0.0372)||
|**_HH main source of income_**|||||
|Commercial farming|||0.1068||
||||(0.0896)||
|Wage employment|||-0.0008||
||||(0.0486)||
|Non-agricultural self-employment|||0.0907**||
||||(0.0420)||
|Remittances & Others|||-0.0092||
||||(0.0966)||
|**_Other source of HH income_**|||||
|Property income and investments|||0.2063**||
||||(0.0846)||
|Transfers and other benefits|||0.1153***||
||||(0.0419)||
|**_HH Asset_**|||||
|Own > median size of land (2.5 acres)|||0.2002***<br>(0.0321)||
|Observations|5,453|5,450|4,105|4,102|
|R-squared|0.3893|0.3896|0.3833|0.7173|

8
# S

reduction and concerted debt rducdon, explain how dhe new menubad approach to debt reduction woiks, and discuss tie reasons why it may domnte te odhe two methods of debt reduction. In section m, we nevw the five recent Brady deals and evaluate our dieoretdcal analysis regarding the workdngs of the menu-bod appoch apins acta picce. Finally, in section IV, we conclude by dfawing lsons from he deas.
- 16 -

**TABLE** 5: TRENDS IN ELECTRONIC INDUSTRIEI

||1981||_Am_<br>_M8_|_nu_|
|---|---|---|---|---|
|- Number<br>of Firms|179|467||590|
|- 4-Firm<br>Concentration<br>Ratio<br>(%):|||||
|Computers|90|43||52|
|Black6White Televisions|32|29||41|
|Printed Circuit Boards|83|S0||54|
|- Value Added Index (1980/81 prices)|100|143||393|
|- Share of Public Sector(%)|43|n.a.|n.a.|32|
|- Imports as percentage of Output||36.7|50.8|45.8|
|- Price<br>Index: Overall|100|102.5|95.7|82.6|
|Consumer<br>Products|100|85.0|76.5|80.0|
|Personal<br>Computers|n.a._L/_|<br>100_La_|41.7|16.7|
|Components|100|97.5|106.5|97.5|

a PCs were manufactured in 1984 for the first time. Source: Joseph (1989).

29. As a result of the liberalization, output in this sector has grown more than 25X p.a. in real terms in the 1980s. Relative prices have declined due to domestic competition, and the share of imports, which first increased due to import liberalization, has started to decline over the last few years. Similarly, high rates of effective protection enjoyed by this sector in the late 1980s started to decline recently.

30. In the automotive subsector, too, competition enhancement through delicensing and the entry of modern cars by Maruti (a public enterprise) forced enterprises to improve their products, with a focus on quality, and to fight for market shares. However, the absolute protection given to automotive products (imports are practically banned) and the absence of minimum efficient scale (MES) thresholds permitted excessive entry of new firms and plants with inefficient sizes and investments too small to ensure competitive productivity and quality. Rationalization of under-sized inefficient producers, especially
The WBES allows to include detailed information on corporate control variables which capture establishment-level differences that could be correlated with firms’ innovation activity and ownership structure. We account for the following firm-specific characteristics: establishment age, size (the number of permanent, full-time employees), and two dummy variables that are equal to1 if the establishment was established through privatization of a state-owned enterprise; and if it is partially government owned. The results show that it is especially important to control for firm size since connected firms are significantly larger in Egypt and firm size is generally positively associated with innovation activity. Moreover, it is critical to be able to control for the extent that some firms are partially government owned and they have been established through privatization as both firm characteristics are likely to be correlated with the ownership of politically connected businessmen as well as innovation activity.

## **4.2 Other data sources**

The WBES for Egypt does not contain information on firms operating in banking and financial sectors. We do, however, have information if establishments included in the survey obtained a credit from some of the major private sector banks. We use information on private sector politically connected banks from Diwan and Schiffbauer (2017). As the large banks are publicly listed, they can observe if they were managed or owned by a government official or if they had a government official as a board member. We use this information to test if politically connected firms superior access to bank loans can (in part) be explained by lending for politically connected private sector banks.

We also use information on politically connected firms in Egypt from Diwan et al. (2015) to check the precision of our measure of political connected firms obtained directly from the 2016 WBES for Egypt. The authors identify connected firms as firms that are managed or owned by businessmen with a high political post in the government or the National Democratic Party or that have such a businessmen as a board member. See Diwan et al. (2015) for details.

# **5. Empirical Specification**

To estimate the effects of cronyism on innovation and outcome variables specific to firms, we consider empirical specifications of the form: 12
**Figure 4:    Construction licenses: Fitted values of corrupt payments vs. official and actual time**

<!-- Start of picture text --> 0 200 400 600 800<br>DB_Constr_permits_time (days)<br>40<br>30<br>20<br>10<br>0<br>40<br>30<br>20<br>10<br>0<br><!-- End of picture text -->

**Figure 5:    Import licenses: Fitted values of corrupt payments vs. official and actual time**

<!-- Start of picture text --> 0 20 40 60 80 100 0 20 40 60 80<br>DB_Import _Lic_time days to get an import license<br>30<br>20<br>10<br>0<br>30<br>20<br>10<br>0<br><!-- End of picture text --> We further subjected the data to tests documented in annex I. We used quadratic functions, added variables controlling for observable country characteristics including population, literacy, characteristics of average firm types and finally added regional dummies. While using further variables leads to different country coverage dependent on availability of controlling variables, typically, we find significant relationships between official procedures and corruption, particularly for construction permits and import licenses. The relationship between bribes and actual time seems more tenuous. Several stories can be told consistent with the data. In the first story regulatory complexity leads to bribes, and bribes are actually effective in removing the obstacle. This could be read to be support for an “effective grease” story. Complex rules are effectively circumvented by bribes. We do not test whether the rules are useful in assuring a relevant dimension of quality, and hence cannot claim direct support for an “efficient grease” hypothesis. Other evidence shows that corruption may create hazards. A case in point is driver licenses in Delhi. Corruption lets people who cannot drive well obtain a license (Bertrand et. al. 2007).

9
|**Table 1. Cur**|**rent Country C**|**overage**|**of the Globa**<br>**# of**<br>|**l Survey of Pu**<br>**# of**<br>|**blic Servant**<br>|**s**<br>|
|---|---|---|---|---|---|---|
|**Country**|**Mode**|**Year**|**institution**<br>**s**|**respondent**<br>**s**|**Respons**<br>**e rate**|**Conducted**<br>**by**<br>|
|Australia|Online|2019|102|104,471|77%|National<br>government|
|Canada|Online|2019|86|182,306|62.30%|National<br>government|
|Chile|Online|2019|66|26,106|43.70%|GSPS|
|Colombia|Online|2019|202|25,082|95.20%|National<br>government|
|Ethiopia|In-person|2016|78|2,195|99.50%|GSPS|
|Ghana|In-person|2018|51|3,343|95%|GSPS|
|Albania|Online|2017|17|3,690|47%|GSPS|
|Brazil|Online|2017|18|3,992|11%|GSPS|
|Estonia|Online|2017|49|3,555|25%|GSPS|
|Kosovo|Online|2017|62|2,465|14%|GSPS|
|Croatia|Online|2017|64|6,711|18%|GSPS|
|Slovak<br>Republic|Online|2017|100|10,817|33%|GSPS|
|Guatemala|In-person|2019|18|3,670|96%|GSPS|
|Indonesia|In-person|2012|15|3,903|83%|GSPS|
|Liberia|In-person|2016|32|2,790|92%|GSPS|
|Lithuania|In-person<br>(via video)|2021|11|956|83%|GSPS|
|Nigeria|In-person|2010|94|5,630|100%|GSPS|
|Philippine<br>s|In-person|2014|7|2,573|100%|GSPS|
|Romania|In-person +<br>online|2019|81|6,037|92% (In-<br>person),<br>24%<br>online|GSPS|
|United<br>Kingdom|Online|2019|106|308,556|67%|National<br>government|
|Ukraine|Online|2018|15|1,802|43%|GSPS|
|United<br>States|Online|2019|45|615,395|42.60%|National<br>government|
|Uruguay|Online|2021|20|10,232|29%|GSPS|
||**Total**||1,339|1,336,227|63%||

<mark>Before providing illustrative insights based on the indicators to motivate future</mark> <mark>scholarly work, several caveats about cross-country comparisons using the data are due.</mark> 11
# **F. Medical Insurance**

Medical insurance has experienced rapid growth and keen competition. It mostly covers group business and seems to be preponderantly oriented toward large employers. In fact, government departments and public sector entities appear to be major clients of medical insurance companies. 5 companies (4 small and 1 medium) do not participate in this branch of business. 47 percent of medical premiums are generated by 5 companies (3 large and 2 medium). Concentration in medical insurance is much higher than in motor insurance (Table 12), as is indicated by a Herfindahl index of 726 (against 450 for motor insurance).

Because it is a group business, medical insurance operates with lower acquisition costs than motor insurance (Table 13). Its reinsurance ratio is higher but has been declining sharply in recent years, probably because reinsurers were not supporting the low premiums charged by primary insurers. The loss ratios and underwriting results are comparable to those of motor insurance. There was a sharp improvement in the technical result in 2002.

**Table 12: Institutional Structure of Medical Insurance, 2002**

|% of|
|---|
|Medical Premiums|
|3 Large<br>32.7|
|8 Medium<br>49.0|
|10 Small<br>18.3|
|HHI<br>726|
|Source: Insurance Commission|

The low level of reserves of medical insurance would merit special attention. Most companies have reserves for outstanding medical claims that are below 10 percent of net incurred claims. In the case of the single foreign company operating in Jordan, the corresponding reserve level is 61 percent. In fact, some companies have outstanding claims reserves that are less than 2 percent of net incurred claims.

The relatively low level of unearned premium reserves could reflect the payment of premiums by quarterly or monthly installments, which would lower the required provisions. In a similar vein, the low level of reserves for outstanding claims could reflect a speedy settlement of most claims. But the generally low level of reserves could also reflect inadequate reserving in the face of overly aggressive competition.

15
Table 4: Impact of civil liberties on the probability of a project being rated as satisfactory, using Probit regression.

|||Specification:|
|---|---|---|
||C|D|
|Freedom House Civil(1 9 7 8 _9 0)b|.018c|.022|
|N=_1155_|(.056)d|(.060)|
|Humana (1982-86)|-.00067|.0012|
|N=604|(.589)|(.388)|
|Media pluralism (1983-90)|.022|.054|
|N=740 -|(.296)|(.045)|
|Freedom to organize (1983-90)|.042|.040|
|N =740|(.009)|(.085)|

Notes: a) for description of the specifications see table 2, b) Annual values from 1978-87 while for the other three indices are single values for the listed time period; c) the value reported is not the Probit coefficient, but the marginal change in the probability of a successful project as the variable changes, evaluated at the means of all independent variables; d) p-levels of the test that the Probit coefficient is zero in parenthesis. Source: Authors' calculations

# **_C)_** Civil liberties and project performance Disentangling **cauIsality**

This empirical relationship between performance of projects and civil liberties is striking. Yet the interpretation of this partial correlation is problematic: it may well be that some country conditions cause both greater civil liberties and better projects. We argue in two ways that the results suggest a causative effect from better civil liberties to better project performance. First, prior work suggests that beneficiary involvement and accountability of is the error standard error, and 4() is the standard normal pdf evaluated at a particular point. Taking the values from the regressions in table 3, the means of ERR from table 1, and an estimate of a gives results from .0266=1.07/14.7*@ ((16.1-10)/14.7) (specification D) and .042 = 1.71/14.7*¢((16.1-10)/14.7) which are slightly higher than the estimates of .018 and .022 from Probit.

- 18 -
In addition to marginal effects, another important perspective to look at is the climate elasticities (the percentage change in net revenues for a percentage change in climate). Because the mean net revenue of irrigated cropland ($1367/ha) is much higher than the net revenue from dryland cropland ($360/ha), the climate elasticities for irrigated land are smaller. For example, the temperature elasticity for dryland is -1.9 but the elasticity for irrigated land is +0.6. This reflects a dryland farm sensitivity to climate that is nearly three times that of irrigated farms and in the opposite direction. The precipitation elasticity for dryland is +0.6 but the elasticity for irrigated land is +0.1. The net revenues from irrigated land are relatively less climate sensitive than those of dryland.

In order to provide a more complete sense of the climate response functions implied in Table 5, we plotted the net revenues of an average farm at different temperatures and rainfall levels. Figures 3a and 3b illustrate the average results for the entire sample of farms (mixing irrigated and dryland farms together). Figures 3a and 3b clearly show that net revenues decline with temperature and rise with precipitation in Africa. The shape of the temperature function, however, is worth noting. Results from Ricardian regressions estimated in the United States (a temperate country) implied a hill-shaped function. Because of its hot initial temperature, Africa lies on the right hand side of this hill, implying warming would have large negative impacts (Mendelsohn et al. 1994; 1999; 2001). Although the results in Africa are consistent with a hill-shaped model, they imply that the net revenues decline gently rather than precipitously. Estimating the Ricardian model with African data reveals that there are additional crops and methods suited to these higher temperatures which may not have been used in a region with a temperate climate such as the US. It is also worth noting with regard to Figure 3b that precipitation increases are generally beneficial to crops in Africa because it is so dry to start with.

Figures 4a and 4b examine the response function of dryland alone. Most African farms use dryland methods so the response function for dryland looks quite similar to the response function for all of Africa. The temperature and precipitation functions are slightly steeper for dryland than for all farms but the difference is not significant.

Figures 5a and 5b illustrate the temperature and precipitation response functions for irrigated cropland. These response functions reveal that higher temperatures reduce net revenues per hectare but at a rate of reduction that is lower than for dryland farms. Irrigated farms appear 14
affiliate operating for 10 years will produce benefits equal to £18,841 per job. In reality, however, it is difficult to ensure that a foreign affiliate that is awarded FDI incentives will remain in operation for a sufficient number of years to warrant the subsidy. Moreover, it is not clear that the investment in question would not have happened in the absence of incentives. On a positive note, the study focuses only on _intra-industry_ spillovers and ignores _inter-industry_ spillovers, which may be larger in magnitude.

A less costly course of action may be to engage in investment promotion activities other than FDI subsidies. The main purpose of investment promotion is to reduce the costs of FDI by providing information on business conditions and opportunities in the host economy and by helping foreign investors address bureaucratic procedures. Investment promotion activities encompass advertising, investment seminars, participation in trade shows, direct marketing efforts, facilitating visits from prospective investors, matching prospective investors with local partners, helping to obtain permits and approvals, preparing project proposals, conducting feasibility studies and servicing investors whose projects have already become operational. Because obtaining information on investment opportunities in developing countries tends to be more difficult than gathering data on industrialized economies, investment promotion should be particularly effective in a developing country context.

The existing evidence from Harding and Javorcik (2011) suggests that 27
The second competitiveness area deals with human capital because a healthy and educated labor force is pivotal to national competitiveness. Pillars 5 and 6 therefore concern health and skills. In this study, these components are indistinctly proxied by human capital (Penn World Table). This index is based on average years of schooling from Barro and Lee (2013), weighted by an assumed rate of return to education based on Mincer equation estimates around the world (Psacharopoulos 1994).

The characteristics of input and product markets are also crucial for productivity and growth. Pillars 7 to 10 therefore look at markets as sources of growth: Pillar 7 deals with the efficiency of product markets and healthy market competition, both domestic and foreign, as drivers of business productivity. For domestic markets, the top marginal income and payroll tax rate (Fraser 2016) and the regulatory quality indicator (WGI) are used as proxies. Regulatory quality captures perceptions of the government’s ability to formulate and act on sound policies and regulations that promote private sector development. In terms of foreign markets, openness is proxied either by the trade-weighted average applied tariff rate (WEF) or by the trade-to-GDP ratio (WEO). Pillar 8 refers to the flexibility of the labor market to quickly shift workers from one economic activity to another at low cost, and to allow for wage fluctuations without much social disruption. This is proxied by the labor market regulation index developed by the Cambridge Business Research (CBR) Center, including the subcomponent related to regulation of work time. The index measures the extent of protection and regulation of work time in the labor code.<sup>5</sup> Pillar 9 deals with efficient financial markets and financial development, proxied here by the ratio of domestic credit to the private sector to GDP (WDI). Finally, Pillar 10 refers to market size (which could be proxied by either GDP or volume of imports), a variable that either coincides or is highly correlated with the dependent variable and was therefore dropped as a determinant.

Finally, the extent to which an economy operates as an innovation ecosystem also matters **.** Pillars 11 and 12 relate to business dynamism and innovation capability; dynamism is proxied here by the cost of starting a business (Doing Business) and innovation by the availability of the latest technology (WEF).

# Methodology

The first part of the analysis relies on the supply-side methodology introduced by Bouis and Duval (2011), Barnes et al. (2013), Johansson et al. (2013) and further elaborated by Egert and Gal (2016). The supply-side framework is based on a production function approach and has the advantage that GDP growth can be expressed as the sum of separable and independent supply-side components. This makes it possible to study separately the link between structural variables and each supply-side channel: labor, capital, and productivity.

Assume a standard Cobb-Douglas production function,

> 5 See Annex **_6_** for details on the CBR labor market regulation index.

8