rafmacalaba/datause-encoder-data huggingface dataset:
|**Table 4: I**|**nteraction w**|**ith theprese**|**nce of credi**|**t bureaus**|||
|---|---|---|---|---|---|---|
|Dependent variable: Woman top|**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|
|manager Y:1 N:0|||||||
||**Panel**|**A: Log odds**|**ratios**||||
|Bank credit (ratio of GDP)*Credit|-2.603**|-2.536**|-4.121***|-3.985***|-4.693***|-4.082***|
|bureau present Y:1 N:0|(1.154)|(1.141)|(1.152)|(1.147)|(1.248)|(1.305)|
|Bank credit (ratio of GDP)|4.111***|4.045***|5.708***|5.387***|6.695***|32.956|
||(0.975)|(1.013)|(0.896)|(0.867)|(1.283)|(20.064)|
|Credit bureau present Y:1 N:0|1.817**|1.789**|2.537***|2.394***|3.001***|2.551***|
||(0.843)|(0.840)|(0.740)|(0.743)|(0.853)|(0.863)|
|GDP per capita (logs)||<br>-0.086|<br>-0.439|<br>-0.230|<br>-1.146|<br>-1.513*|
|||(0.651)|(0.965)|(0.900)|(0.932)|(0.913)|
|Number of workers (logs)||<br>-0.200***|<br>-0.231***|<br>-0.200***|<br>-0.197***|<br>0.021|
|||(0.050)|(0.065)|(0.064)|(0.064)|(0.155)|
|Age of firm (logs)|||-0.084|-0.107|-0.112|-0.363|
||||(0.111)|(0.116)|(0.116)|(0.307)|
|Labor productivity (logs)|||-0.017|0.007|-0.009|0.136|
||||(0.048)|(0.049)|(0.047)|(0.102)|
|Women owners Y:1 N:0|||<br>2.560***|<br>2.662***|<br>2.664***|<br>2.675***|
||||(0.140)|(0.155)|(0.155)|(0.156)|
|Women workers (proportion)|||<br>1.491***|<br>1.498***|<br>1.534***|<br>1.552***|
||||(0.215)|(0.211)|(0.214)|(0.216)|
|Exports (direct, share of sales)|||-0.108|-0.108|-0.117|-0.084|
||||(0.245)|(0.240)|(0.240)|(0.237)|
|Foreign ownership|||<br>0.291|<br>0.332|<br>0.338|<br>0.324|
||||(0.304)|(0.307)|(0.308)|(0.304)|
|Quality certification Y:1 N:0|||0.104|0.128|0.128|0.139|
||||(0.139)|(0.138)|(0.138)|(0.138)|
|Overdraft Y:1 N:0||||-0.086|-0.092|-0.099|
|||||(0.128)|(0.128)|(0.127)|
|Multi establishment firm Y:1 N:0||||<br>0.113|<br>0.068|<br>0.088|
|||||(0.174)|(0.176)|(0.175)|
|Obtaining license is a major||||<br>0.088|<br>0.093|<br>0.091|
|<br>obstacle Y:1 N:0||||(0.187)|(0.188)|(0.188)|
|Losses from power outages||||<br>1.493*|<br>1.625**|<br>1.834**|
|||||(0.800)|(0.781)|(0.805)|
|Firm audited Y:1 N:0||||<br>-0.073|<br>-0.075|<br>-0.068|
|||||(0.118)|(0.118)|(0.118)|
|Registered when started Y:1 N:0||||<br>0.035|<br>0.024|<br>-0.004|
|||||(0.216)|(0.216)|(0.213)|
|Legal form fixed effects||||Yes|Yes|Yes|
|Visited by tax officials Y:1 N:0||||-0.019|-0.010|-0.018|

42
**Figure 12 - Labor Taxation is Higher for Low-Wage Earners in ECA Countries** Labor taxes, 2007

<!-- Start of picture text --> 45%<br>35%<br>25%<br>15%<br>5%<br>-5%<br>Percentage of Labor Taxes<br><!-- End of picture text --> Source: Koettl and Weber (2012) based on OECD Tax and Benefit model.

Note: Columns represent the tax wedge for low-income earners (singles with no children at 33 percent of average wage) in 2008 (for Bosnia, Macedonia, and Serbia, 2009).

The historical reliance of ECA countries on labor taxation cannot be easily disentangled from the generous social insurance systems. A redesign of tax systems aimed at reducing social contributions will need to be balanced with expenditure demands, fiscal constraints and the existing tax structure. Within this overall fiscal framework, countries may be able to facilitate the moving of workers to cleaner industries through the use of well designed tax incentive schemes.

It is important to recognize that in many countries high labor market flexibility often does not go hand in hand with generous social protection systems; however, this does not need to be the case. Overall, there is a negative correlation between flexibility and protection across countries. This correlation is even stronger when considering only high-income countries. As incomes increase, countries gravitate toward one of two work models: one that forgoes flexibility or another that forgoes protection. In that sense, transition countries might in the future embark on a pathway towards one of the two work models. Some already seem to have chosen—like Georgia seems to have chosen the high flexibility/low protection model, and Slovenia the low flexibility/high protection model (World Bank, forthcoming). Nevertheless, some countries, like Denmark, Austria, Switzerland, and Ireland to a lesser extent - have managed to find a balance between flexibility and protection. A reform of labor market institutions needs to be balanced: increasing labor market flexibility should be accompanied by (i) other reforms that improve the overall business environment and (ii) improving the safety nets available for workers when they are out of work. The 'flexicurity' model in Denmark is a benchmark of getting this balance right (See Box 2).

24
# **8.2  Identifying Critical Road Links**

Since our methodology ties forest clearing impacts to specific road links, we can also use our high-resolution database to grade those links by expected biodiversity losses when upgrading occurs. We compute mean expected losses in corridors extending 10 km on either side of the Delorme-identified secondary road links in moist forest areas. We normalize to the range [0100] for ease of comparison. Figures 21-23 identify the road corridors where a generalized road upgrading program is expected to produce the greatest losses in biodiversity value.<sup>12</sup> The maps highlight the highest four deciles (purple (90-100); red (80-90); orange (70-80); yellow (60-70)), along with primary road links where upgrading does not occur (blue).<sup>13</sup> In Bolivia (Figure 21), the largest clusters of critical road links are in the center-north and far south, with smaller clusters visible in the north, east and west. Their relatively skewed spatial distribution reflects Bolivia’s skewed area distribution of expected losses (Figure 18). In contrast, the distribution of critical corridors in Cameroon (Figure 22) reflects its more evenlydistributed expected losses from road upgrading (Figure 22). Road clusters in the most critical (purple) category are visible in the southwest, west and north, frequently alongside red clusters. Critical links in the lower priority (orange and yellow) categories are more widely scattered.

Like Cameroon, Myanmar (Figure 23) exhibits a more even distribution of critical road corridor clusters than Bolivia. Large clusters of the most critical (purple) corridors are visible in the east, with smaller clusters linked to next-priority (red) corridors in the north, west and south. Again, clusters in the lower priority categories (orange and yellow) are widely scattered.

> 12 This exercise focuses on the impact of generalized secondary road upgrading.  It incorporates a network analysis methodology that can also be used to estimate expected losses associated with upgrades from secondary to primary status in individual road corridors.  This would entail identifying all road segments linked to the closest urban market via these corridors, calculating the change in distance shares for the relevant secondary and primary road links, and predicting the forest clearing impact in all cells lying closest to the affected road links.

> 13 Many Delorme road links are short; long colored road lengths in Figures 21-23 incorporate successive short links.

52
# **Figure 14: Direct labor content per $100 of gross exports across sector 2011**

<!-- Start of picture text --> Agr, Forestry, Fisheries<br>Beverages and Tobacco Products<br>Chemical, Rubber, Plastic Products<br>Construction<br>Dwellings<br>Electricity, Gas, Water<br>Energy Extraction<br>Ferrous Metals<br>Leather Products<br>Machinery and Equipment nec<br>Manufactures nec<br>Metal Products<br>Metals nec<br>Mineral Products nec<br>Minerals nec<br>Other Private Services<br>Paper Products, Publishing<br>Processed Foods<br>PubAdmin/Defence/Health/Educat<br>Textiles<br>Trade and Transport Services<br>Transport Equipment<br>Wearing Apparel<br>Wood Products<br>0 20 40 60 80<br>Direct LVAX share (%)<br>ZAF BRA RUS IND CHN<br><!-- End of picture text --> <!-- Start of picture text --> Agr, Forestry, Fisheries<br>Beverages and Tobacco Products<br>Chemical, Rubber, Plastic Products<br>Construction<br>Dwellings<br>Electricity, Gas, Water<br>Energy Extraction<br>Ferrous Metals<br>Leather Products<br>Machinery and Equipment nec<br>Manufactures nec<br>Metal Products<br>Metals nec<br>Mineral Products nec<br>Minerals nec<br>Other Private Services<br>Paper Products, Publishing<br>Processed Foods<br>PubAdmin/Defence/Health/Educat<br>Textiles<br>Trade and Transport Services<br>Transport Equipment<br>Wearing Apparel<br>Wood Products<br>0 20 40 60 80<br>Direct LVAX share (%)<br>ZAF COL CHL PER THA TUR<br><!-- End of picture text --> _Source:_ Authors’ elaboration based on LACEX.

Figure 15 shows this comparison across all countries for 2001 and 2011 for the three largest South African export sectors. In machinery and equipment, South Africa’s labor content as a share of exports declined relative to the average in the other countries, although it remains still slightly above the level expected given its income per capita. In metals, the country has moved from being 24
# **Which** Firms Do Foreigners Buy? Evidence from Korea

Caroline FReund Simeon Djankov*

* Federal Reserve Board, World Bank and CEPR, respectively. We axe grateful to Stijn Claessens, Joshua Coval, Simon Evenett, Sung Kwack, Guy Stevens, Bernard Yeung, Kei-Mu Yi and participants at conferences at the University of Michigan and the Federal Reserve Bank of Chicago. The views in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System or the World Bank, or any other persons associated with these institutions. Correspondence: Caroline.L.Freund@frb.gov.
change of manager, with most (74 percent) managers appointed by the government, but some selected through bidding (17 percent),<sup>6</sup> or elected by the employees (5 percent). The form of managerial selection varied according to the level of government overseeing the SOE. The more local the government, the more likely it was that the CEO was determined by bidding rather than being appointed.

**Table 1. Characteristics of Performance Contracts**

||_Pooled_<br>_Sample_|<br>_central_<br>_gov't_|_Firms Gove_<br>_provincial_<br>_gov't_|_rned by:_<br>_municipal_<br>_gov't_|_county_<br>_gov't_|
|---|---|---|---|---|---|
|Number of PC-participants|628|52|<br>64|450|<br>54|
|by how the CEO was generated:||||||
|%: appointed by government|.740|.942|<br>.859|<br>.733|<br>.500|
|%: generated by bidding procedure|.169|.000|<br>.063|<br>.173|<br>.389|
|%: elected by all employees|.049|.038|<br>.047|<br>.047|<br>.093|
|by the Primary PC target:||||||
|%: Profits|.422|.385|<br>.406|<br>.433|<br>.407|
|%: Tax|.279|.192|<br>.219|<br>.313|<br>.148|
|%: Quantity|.260|.327|<br>.312|<br>.227|<br>.370|
|The share of PC-participants posting bond|.282|.019|<br>.172|<br>.280|<br>.648|
|The average bond for bond-posting firms<br>(in 1,000 yuan)|32.4<br>I|13.0|<br>34.7|<br>36.1|<br>22.2|

Note. Based on the authors' calculation from _A Survey of Chinese SOEs: 1980-89._ In a few cases (16 percent of the companies) the manager posted a bond that was forfeited if he failed to achieve the contract's goals. As with bidding, posting a bond was more likely, the more local the government authority. The amounts are non-trivial, averaging about 32,400 yuan, several times a CEO's annual wages. SOE managers nder 6This category also includes those firms whose managers were directly appointed by the contract signer.

8
<!-- Start of picture text --> COC ___<br>OO _—_—:2<br>i —<br>tO _—_<br>a<br>it<br>WW<br>——<br>nt ><br>hs<br>mm<br>Kuwait<br>Morocco —<br>libya =<br>Saudi Arab<br>Ageia<br>Bahrain<br>UAE<br>Qatar<br>Djibouti #<br>0 5 10 15<br>Rate of motor vehicle air pollution deaths<br>(per 100,000)<br><!-- End of picture text -->
in a district _d_ , state _s_ , industry _j_ and year _t_ as the dependent variable. The specification takes the form: We include a vector _Xi_ of plant inputs into the production function: log employees, log book values of capital, and log costs of materials. We exclude plants with missing values for these metrics. Because we rely on revenue data to calculate productivity, we face a common limitation in the literature that we cannot separate the efficiency or productivity of plants in terms of real inputs and outputs from other factors like their mark-ups or quality (e.g., Foster, Haltiwanger, and Syverson 2008, De Loecker 2011). Regressions include state-industry-year fixed effects  _s_ , _j_ , _t_ to capture regular differences in production techniques and spatial locations across industries. Industries for this purpose are defined at the four-digit NIC level. We study two district traits in the _Zd,t_ vector—the share of local manufacturing employment that is in the informal sector and the share of local informal employment that is contained in 1-person firms. We use establishment weights from the surveys to weight plants, and we report standard errors clustered by district-industry. Table 8a presents results for urban areas only, while Table 8b presents results for rural areas. It is important to note that our key explanatory district traits in the _Zd,t_ vector are calculated over the whole district rather than separately for urban and rural areas.

In both tables, Column 1 provides a baseline estimation of the plant-level production function before district-level conditions are incorporated. These underlying parameters for the production function, emphasizing employees and materials, are very stable across estimations in both urban and rural areas. Column 2 of Table 8a shows that 1-person firm productivity tends to be higher in locations with significant shares of informal activity in urban areas, which suggests some form of agglomeration effects are at play. This relationship is reversed in rural areas, where 1-person firms have lower productivity when informality is a greater share of local activity, suggesting that complementarities with larger informal firms are not at play in rural areas the 17
# **From Creativity to Innovation**

By Shahid Yusuf* Commercially viable innovations are becoming the hinge of success in global markets and by helping to raise total factor productivity, they now account for a significant share of growth in advanced and industrializing economies.<sup>1,2</sup> Innovation can take many forms among which product innovation is but one. Design and incremental process innovations are more common and in recent years, myriad innovations are being introduced by providers of services.<sup>3</sup> Innovation is changing the structure and enhancing the capabilities of organizations.<sup>4</sup> Moreover, institutional innovations are sharpening market incentives for entrepreneurial activity and technology trading which take new ideas, products and practices into the commercial domain.

In certain areas such as genetics, climatology and the social sciences, innovative uses of computing power are making research more productive by automating the framing of multiple hypotheses and their testing using advances in data processing and in evaluative algorithms (Glymour 2004). Needless to say, the significance of innovation for economic performance and living conditions can scarcely be overemphasized in the face of the opportunities presented by globalization, and the multiple challenges arising from resource scarcities, the dire predictions of accelerating climate change and the threat of pandemics caused by new organisms.

Innovation springs from the creative application of knowledge. Thus, it has two essential ingredients – creativity - artistic, scientific or other<sup>5</sup> - and the stock of knowledge. Knowledge and the “functionalities” it supplies is the essential raw material

> * Kaoru Nabeshima offered insightful comments and Marinella Yadao provided efficient and cheerful assistance with the production of the paper. I am deeply grateful to both.

> 1 Smil (2006) provides an enlightening tour of the innovations which transformed the twentieth century. 2 See for instance OECD (2006, II, ch3); and Phelps (2007) who attributes the “root problem” of the European economies as being the low rate of commercially successful innovations.

> 3 Innovations in financial, retailing, wholesaling and IT based services have stimulated the growth of productivity in the U.S. over the past decade (Solow 2001).

> 4 Since the mid-1980s, the crafting of new business models and organizational forms has become a flourishing industry which has encouraged firms to experiment so as to pare costs, increase flexibility and raise productivity.

> 5 Mokyr 2005b provides a historical perspective on creativity and how the competitive market for ideas which emerged in seventeenth century Europe contributed to it.

1
# Table 8

# Decomposition of Change Over Time in **Womenas** Fraction of the Wage Employaent, Within and Between Sectors, by Region

|Sectors and<br>Region of<br>Countries|Women as<br>a Fraction of<br>Labor Force|Average<br>Rate of Change<br>in Fraction(%)|Percent o<br>Intrasector<br>Change|f Chanae due<br>Intersector<br>Change|to:e<br>Residual<br>Interaction|
|---|---|---|---|---|---|
|Agricultural/Nonag|riclultural<br>Sect|orsa||||
|World Sample|.32|<br>.13|71|31|-2|
|High Income|.36|<br>.35|94|6|-O|
|<br>Latin America|.27|<br>.29|45|42|13|
|Africa|.09|<br>.09|17|81|2|
|East Asia|.34|<br>.21|107|-5|-1|
|South & West Asia|.26|<br>-.52|109|-13|4|
|Agriculture and Sev|en Other Sector|sb||||
|World Sample|.32|<br>.13|-11|119|-8|
|High Income|.36|<br>.35|48|54|-2|
|<br>Latin America|.27|<br>.29|-9|111|-2|
|Africa|.09|<br>.09|97|23|-21|
|East Asia|.34|<br>.21|114|-5|-9|
|South & West Asia|.26|<br>-.52|109|-12|3|

'Agriculture includes forestry and fishing.

bNonagriculture divided into the following ISIC categories: Mining; manufacturing; electricity, gas, and utilities; construction; wholesale and retail trade; transportation; business and personal services.

"Percent of changes due to the three components may not precisely sum to onr because of rounding. The change in workers in wage employments is summed across countries before total changes in the share of wage earners are calculated and decomposed for the sample and for the regional aggregations of countries.

See Appendix Table A-1 for composition of sample.
price). In the value chain analysis, this high price is compensated for by reducing the ginner’s investment in out-grower extension and other services, thereby threatening the sustainability of high quality and productivity in the cotton sub-sector.

**Figure 25: Comparison of un-ginned cotton SV at farm level and parity prices** **<u>(USD/ton)</u>**

<!-- Start of picture text --> Cotton, Comparision of Farm Gate SV Un-ginned seed cotton farm-gate prices, US$/tone<br>(USD per MT un-ginned seed cotton)<br>600 600<br>500 500<br>400<br>400<br>300<br>300<br>200<br>200<br>100<br>100 0<br>-<br>Malawi Mozambique Zambia (2006/07) Nigeria Brazil Cameroon<br>(2007/08)<br>Malawi 2006Malawi 2007/08Mozambique 2006/07 Nigeria 2006Zambia 2006/07Cameroon 2007 Brazil 2006<br>FAM(L) FAM(H) FAM ECF FAM(L) FAM(H) Yield Prog FAM LCF FAM(L) FAM(H) COM<br><!-- End of picture text --> 94. When we compare the total SV against the export parity, as shown in Table 23, Malawi’s competitive edge is very narrow. In fact the results indicate that in 2006 and 2007, ginners may have been uncompetitive. Among other reasons, this is due to the high producer price and the low ginning-out-turn (GOT).

**Table 23: Comparison of final cotton SV and parity** **<u>prices</u>**

|||<br>**E**|<br>**xport Parit**|<br>**y**|<br>**Competit**|<br>**iveness Ga**|<br>**p/Edge**|
|---|---|---|---|---|---|---|---|
||**Final SV**|Dec 06|Oct 07|June 08|Dec 06|Oct 07|June 08|
|FAM-low|1,353|101198|116311|136112|(341.30)|(190.16)|7.85|
|FAM-high|1,360|,.|,.|,.|(347.66)|(196.53)|1.48|

95. As shown in Table 24, one of the ways to consolidate and sustain competitiveness in cotton is to improve the ginning out turn (GOT). A 1% improvement in the GOT substantially lowers per unit ginning costs and thus enhances the ginners’ profit. This is an area that provides the greatest scope in terms of improving the ginner’s profit which could then be rolled-back to the net farmer profit through investment in services required to improve the quality and yield of seed cotton and lint. GOT may easily be improved at the farm-level through the use of treated seed, improving the use of chemicals through appropriate scouting for pests so as to ensure timely application of chemicals, avoiding contamination of the seed cotton at picking, sorting, baling as well as transportation to the ginnery. At the gin-gate, GOT may be improved by use of better gins and avoiding contamination through better grading and handling techniques. With the GOM’s current pricing policy whereby nearly all profits in the cotton value chain accrue to farmers, however, there is little scope for ginners to invest in improved farmer extension or upgrading of ginning facilities.

46
-22 -

Albania - the Critical Imports Project in 1992 - included an irrigation component for the most urgent repairs to infstructure and also provided funds to prepare a Water Code and legislation for Water Users' Associations). A proposed $10 million Intemational Development Association credit is presently being appraised by the Bank for rehabilitation of irrigation and drainage systems serving some 57,000 farm families in 7 districts in the coastal plains.

41. At present there are 37 district-based Water Enterprises, although it is suggested that these Enterprises might evenually be merged into larger organizations covering the main river basins in the country. The Water Enterprises in turn sell water on a wholesale basis to emerging Water Users' Associations, which are based on villages. Although the irrigation system was previously based on cooperatives and state farms whose boundaries did not necessarily coincide with those of villages, after the pivatization of agriculture, the villages were found to be the only well-fnctioning local social unit in the countryside. The Water Users' Associations are comprised of elected village representatives who consolidate water purchases from individual farmers, collect water fees and enter into contracts with the Water Enterprises for scheduled deliveries.

42. Transport Of the **various** means of transport, local govenments have no responsibility for mae transport, ports and railroads, but they do have responsibility for local roads. Roughly 8,200 km of the toal naional road network of 18,000 km. are classified as "local' roads connecting small urban centers with rura communities. A fur-ther 7,800 km. of "main" roads connect main cities with each other, and the 1,800 m. of "economic" roads serve industrial and mining centers. Excluding the economic road network, local roads constiu 51% of the road network but are allocated roughly 30% of total road expendiures in the national Budget. Owing to economic stringency, most road expenditures have been