rafmacalaba/datause-encoder-data huggingface dataset:
for power generation. Domestic gas fields produce nearly 1 trillion cubic feet (TCF) of natural gas but known reserves hold only 11TCF of gas. Production will peak in 2018 and begin to decline thereafter, dropping to less than 10% of current output by 2030. Natural gas accounts for 57% of countries Total Primary Energy Supply and power sector consumes roughly 40% of gas supplied. In all scenarios, we assumed that domestic gas availability for power generation will decline at the rate projected for overall gas supply.

Figure 7. Fuel price assumptions<sup>11</sup> <!-- Start of picture text --> 25 Fuel Oil Diesel<br>Domestic coal Import Coal<br>Domestic gas LNG<br>20<br>15<br>10<br>5<br>0<br>2015 2017 2019 2021 2023 2025<br>US$/MMBtu<br><!-- End of picture text -->

# Transmission

The power network in the transmission analysis is based on the existing grid and plans for additional substations and transmission lines. The input dataset consists of information on each 132 kV, 230 kV, and 400 kV substation and transmission lines connecting them. Each line’s rating is taken into account. The transmission network is analyzed using PSS/E, which permits the assessment of system operation under different generation, transmission and load scenarios and the system’s viability under different configurations. The results from the generation and dispatch model provides the input on generation, while substation loads were scaled uniformly according to the projected growth in overall demand.

# Spinning reserves

Spinning reserve management in Bangladesh faces a fundamental issue due to the absence of participation by most plants in frequency support. Until recently, frequency fluctuations of ±2 Hertz (Hz) had regularly occurred in recent years due to the lack of automatic (load) frequency control mechanism. The system operator now limits frequency variations to within ‐1.5 Hz and +1 Hz. A group of six plants provide frequency response jointly. However, when frequency drops below 48.5 Hz, the operator relies on large‐scale load shedding to maintain stability.

When considering solar and wind deployment, we introduce a spinning reserve requirement to cover 7% of potential solar and wind generation. This means that up to 7% of potential solar generated needs to be covered by fast reacting power generation capacity to account for unexpected changes. Spinning reserve

> 11 World Bank. “World Bank Commodities Price Forecasts (January 2017)” 2017. Source: <u>http://pubdocs.worldbank.org/en/926111485188873241/CMO‐January‐2017‐Forecasts.pdf</u>

12
3 have become large and powerful institutio-is in the last three decades. Typically these are defined benefit pension plans, which provide workers an annual benefit accrual (usually a function of pay and years of service). This accrual converts into a retirement annuity payment when the employee attains a specified age and service under the plan. Recent surveys (see Table 1) show that there are approximately 2,400 public pension systems in the U.S., coveting about 10 million full-time public sector employees and about 3 million pension beneficiaries -- mainly employees of state and local 'overnments, and often teachers and other school employees, police and firefighters, judges, correctional officers, and other public servants.' These plans pay relatively generous benefit levels, amounting to some 40% of pre-retirement pay at relatively young retirement ages; usually PERS retirement benefits are at least partially indexed to inrlation.

Benefit promises which accrue under PERS plans are liabilities that the sponsor is expected to pay retirees at some future date. Practice varies as to whether public employers back up these promises by making payments to a segregated pension trust fund, which are then invested to generate eventual benefit payments. Many PERS plans have succeeded in amassing substantial funds: in the U.S., public pensions held about $730 billion at the end of the 1980's, accounting for _5%_ of the country's total financial assets, 13% of all domestic bonds, and almost 8% of all domestic equities (Hoffman and Mondejar 1992).

A major responsibility of those charged with managing public sector pensions is to direct the inves .nent of these assets. Research suggests that PERS funds have been Olivia S. Mitchell - Pu, c Pension C ance and Performance
De Loecker, J. (2013). Detecting learning by exporting. _American Economic Journal: Microeconomics_ , _5_ (3), 1-21.

<mark>Fisher-Vanden, K., Jefferson, G. H., Jingkui, M., & Jianyi, X. (2006). Technology development and energy productivity in China.</mark> _<mark>Energy Economics</mark>_ <mark>,</mark> _<mark>28</mark>_ <mark>(5-6), 690-705.</mark> Foster, L., Grim, C., Haltiwanger, J. C., & Wolf, Z. (2018). _Innovation, productivity dispersion, and productivity growth_ (No. w24420). National Bureau of Economic Research.

Galasso, A., & Simcoe, T. S. (2011). CEO overconfidence and innovation. _Management Science_ , _57_ (8), 1469-1484.

Girma, S., & Gorg, H. (2007). Multinationals' Productivity Advantage: Scale or Technology?. _Economic Inquiry_ , _45_ (2), 350.

<mark>Gordon, R. J. (2012).</mark> _<mark>Is US economic growth over? Faltering innovation confronts the six headwinds</mark>_ <mark>(No. w18315). National Bureau of Economic Research.</mark> <mark>Gordon, R. J., & Sayed, H. (2019).</mark> _<mark>The industry anatomy of the transatlantic productivity growth slowdown</mark>_ <mark>(No. w25703). National Bureau of Economic Research.</mark> Gort, M., & Klepper, S. (1982). Time paths in the diffusion of product innovations. _The economic journal_ , _92_ (367), 630-653.

Griliches, Z. (1986). Productivity, R and D, and Basic Research at the Firm Level in the 1970s. _The American Economic Review_ , _76_ (1), 141-154.

Hall, B. H. (2011). _Innovation and productivity_ (No. w17178). National bureau of economic research.

<mark>Hardy, M., & McCasland, J. (2016). It takes two: experimental evidence on the determinants of technology diffusion.</mark> _<mark>Unpublished paper, University of British Columbia</mark>_ <mark>.</mark> <mark>Hegde, D., & Shapira, P. (2007). Knowledge, technology trajectories, and innovation in a developing country context: evidence from a survey of Malaysian firms.</mark> _<mark>International Journal of Technology Management</mark>_ <mark>,</mark> _<mark>40</mark>_ <mark>(4), 349-370.</mark> Hendry, D. F., & Krolzig, H. M. (2004). We ran one regression. _Oxford Bulletin of Economics and Statistics_ , _66_ (5), 799-810.

Hoover, K. D., & Perez, S. J. (1999). Data mining reconsidered: encompassing and the general‐ to‐specific approach to specification search. _The econometrics journal_ , _2_ (2), 167-191.

<mark>Hsieh, C. T., & Klenow, P. J. (2009). Misallocation and manufacturing TFP in China and India.</mark> _<mark>The Quarterly journal of economics</mark>_ <mark>,</mark> _<mark>124</mark>_ <mark>(4), 1403-1448.</mark> <mark>Juhász, R., Squicciarini, M. P., & Voigtländer, N. (2020).</mark> _<mark>Technology Adoption and Productivity Growth: Evidence from Industrialization in France</mark>_ <mark>(No. w27503). National Bureau of Economic Research.</mark> Kumar, N., & Aggarwal, A. (2005). Liberalization, outward orientation and in-house R&D activity of multinational and local firms: A quantitative exploration for Indian manufacturing. _Research Policy_ , _34_ (4), 441-460.

19
# **Box 3. The telecommunications boom**

**In the 1990s, telecoms were opened to competition.** In 1990, despite the estimated 800,000 applicants, the sole dominant provider (PLDT) took years to install a line, and tele-density was at 1 per 100 persons. The deregulation shook the industry, from the dominance of a single operator to increased market competition, dynamism and vastly improved access to telecommunication services. By 2006, there were 6.5 million fixed lines installed, tele-density had climbed to 7.7 and the waiting time for phone service was measured in days. Mobile penetration grew exponentially, from 3 million mobile phones in 1999 to over 35 million in 2006. New investors came steadily into the market, which now counts on 73 local exchange carriers, 11 international gateway facilities (IGFs), 7 mobile telephones, 14 inter-carriers, and 388 valueadded service (VAS) providers.

**Today one of the most dynamic industries, telecommunication employs more than 20,000 people.** The Philippines is now an important location for new growth industries such as BPO, medical transcription and call centers, and other IT-enabled retail services, such as mobile-phone-based business solutions (e.g., through mobile phones, remittances charges are 1 percent of the average remittance value, while banks charge up to six times more). By 2006, the sector accounted for 5 percent of GDP, corporate profits had increased to $3.3 billion, and an estimated 235,000 jobs are found in industries that have benefited from the telecoms reforms.

_Source:_ Mirandilla 2006, World Bank, 2007, Bernardo and Tang, 2007.

**... but leadership matters.** To break monopolies and increase competition in protected sectors, a clear vision, political will, and a coherent implementation strategy are needed (Bernardo and Tang, 2007).<sup>48</sup> In agriculture, import protection for rice should be gradually reduced, and public investments should be geared towards reducing farmers’ marketing and transaction costs. The NFA should devolve its rice trade functions to the private sector and focus on market regulation. In the transport sector, to promote full competition in foreign containerized cargo operations, ports and airlines licensing should be increased. The PPA’s port development and operating functions should be separated from its regulatory function. The aviation sector should be liberalized further, as competition would reduce airfares and increase the number of tourists. Greater access to bank lending for unconnected companies (foreign corporations, domestic medium and small firms) should be promoted. The government should open the domestic market to cement imports, to contain price increases, and simplify the numerous regulatory, land, quarrying and environmental clearances required in setting up a cement plant, to encourage new domestic and foreign entrants. Finally, a reform of the labor market is overdue, by removing protections, streamlining enforcement agencies, and lowering wage pressures.

> 48 According to Bernardo and Tang (2007), the electoral rules should attract qualified candidates and select contenders that think long-term.

42
||||**Table A.5**|**continued**||||||
|---|---|---|---|---|---|---|---|---|---|
||**(1)**<br>**Item**||**(2)**<br>**Repre**|**(3)**<br>**sentative s**|**(4)**<br>**ample**||**(5)**<br>**Dua**|**(6)**<br>**lpractice s**|**(7)**<br>**ample**|
||**diiit**||||Diff||||Diff|
||**scrmna**<br>**ion tercile**|All|Public|Private|erence<br>(3)-(2)|All|Public|Private|erence<br>(6)-(5)|
|**Panel C: Dysentery**||||||||||
|_History questions_||||||||||
|age of child|low|0.919|0.795|0.945|0.150***|0.930|0.921|0.939|0.019|
|qualities of stool|low|0.167|0.077|0.186|0.109**|0.271|0.159|0.379|0.220***|
|frequency|medium|0.288|0.179|0.311|0.132**|0.372|0.270|0.470|0.200***|
|quantity of stool|high|0.050|0.000|0.060|0.060*|0.031|0.016|0.045|0.030|
|urination|high|0.018|0.000|0.022|0.022|0.008|0.016|0.000|-0.016|
|active/playful|high|0.032|0.026|0.033|0.007|0.000|0.000|0.000|0.000|
|fever|medium|0.171|0.077|0.191|0.114**|0.295|0.222|0.364|0.141**|
|abdominal pain|low|0.113|0.077|0.120|0.043|0.256|0.222|0.288|0.066|
|vomiting|low|0.216|0.077|0.246|0.169***|0.295|0.254|0.333|0.079|
|source of water|high|0.023|0.000|0.027|0.027|0.016|0.000|0.030|0.030*|
|what has eaten|medium|0.050|0.000|0.060|0.060*|0.093|0.032|0.152|0.120***|
|taking fluids|medium|0.023|0.000|0.027|0.027|0.062|0.048|0.076|0.028|
|_Number of observations_||222|39|183||130|63|67||

Notes: 65
# **Table 3.1. OLS results**

_Dependent variable: Number of sales to legal entities per 100,000 residents for industrial and other special uses and purposes_

||Model 3.1.1|Model 3.1.2|Model 3.1.3|
|---|---|---|---|
|Constant|41.71<br>(52.02)|55.42<br>(59.25)|39.37***<br>(9.51)|
|Administrative land pricing factor in<br>the regional capital|-0.55**<br>(0.20)||-0.79*<br>(0.36)|
|Ln duration of land sale transaction<br>procedure(Proc. 3A,ARCS)||-3.86<br>(2.43)|-2.62<br>(2.11)|
|Ln regional GDP per capita|-2.40<br>(4.59)|-2.22<br>(5.21)||
|Adj. R<sup>2</sup>|0.345|0.069|0.356|
|N|14|13|13|
|Mean of the dependent variable|8.99|9.68|9.68|

*, **, *** Significance level of 10%, 5%, and 1%, respectively

In order to validate the above results, we used a larger set of data collected from official statistical sources. Unfortunately, only a limited number of variables used in the previous models were available from official sources, so where possible, we tried to confirm the survey results with approximation variables available from the official statistics. Using official data, we tested the following model as an extension of the Model 3.1.1 described above: where: Θ is a vector of control variables from a list shown in the Annex; and ρ is still the administrative land pricing factor in the regional capital.

Table 3.2 shows that the pricing factor imposed by regional authorities is still highly significant (actually this variable has a higher significance in “whole country” setting than in the smaller sample of surveyed regions). Increases in the level of the pricing factor negatively influence the number or privatized land plots. In this larger set of observations the significance of other controls is also increasing. The only unexpected result is the change of sign for regional income (Ln of regional GDP) which becomes positive instead of negative in the earlier models. This, perhaps, can be explained by the rather limited number of observations used to test Models 3.1.1 through 3.1.3.

For the models in Table 3.2, the main factor influencing the land privatization level in any region is the pricing policy implemented by authorities. This policy is expressed as a multiple of the land tax rate per square unit (meter) of a land plot (i.e. a land price factor of 17 means that municipal authorities price a square meter of land at seventeen times the land tax rate for this land plot). The latter means that, other things being equal, a reduction in the land price factor by one standard deviation, (e.g., from about 10 to about 6), would increase the number of land 14
over 70% of households, cooking, washing, cleaning and taking care of small children is done solely by women<sup>7</sup> .

# **PART II. ENTREPRENEURSHIP AND LEADERSHIP AMONG MEN AND WOMEN**

# **2.1 Entrepreneurship among Men and Women**

Men are almost twice as likely to engage in entrepreneurial activities as women (Figure 5). In fact, men represent 72% of the people who identify themselves as self-employed. Furthermore, self-employed men are significantly more likely to hire workers than self-employed women. Men comprise over two-thirds of entrepreneurs with employees.

**Figure 5. Structure of men’s and women’s employment,%** **<u>(population age 15 and above)</u>**

<!-- Start of picture text --> 100<br>4.65<br>90 14.33 unpaid family worker<br>80<br>70<br>60 66.44 employees<br>50 70.75<br>40 self-employed<br>30 without employees<br>20<br>24.41 self-employed with<br>10 12.74<br>0 4.5 2.17 employees<br>Men Women<br><!-- End of picture text --> Source: Serbia LFS, 2009 Almost 70% of the self-employed live in rural areas and over a half of entrepreneurs of both genders are employed in agriculture. According to the UNDP study “The position of women in the labor market in Serbia”, women’s entrepreneurship in rural areas is constrained by the limited ownership of farm land. When rural women buy or inherit land, tradition obliges them to register it in the name of their husband or other male relative. This situation prevents women living in rural areas from starting/joining agricultural cooperatives<sup>8</sup> . It may also limit their opportunities for engaging in other types of entrepreneurial activities due to lack of collateral and inability to access bank loans.

Noticeable differences can be observed in the concentration of male and female entrepreneurs in nonagricultural activities. Self-employed women significantly outnumber men in trade, real estate and renting as well as in community, social and personal services while the number of men entrepreneurs is almost double that of women in manufacturing, construction and transport and communications (Annex 3).

The analysis of the Business Environment and Enterprise Survey (BEEPS) 2009 provides additional information on the experience of male and female-owned firms in the non-agricultural sector. The survey helps assess the performance and key obstacles to growth of SMEs and large firms in Serbia through interviews with the owners and top management of 388 companies in manufacturing and services sectors.

> 7 Babovic, Marija. 2008. _The position of Women on the Labor Market in Serbia._ UNDP and Gender Equality Council of the Government of  Serbia, Belgrade

> 8 Babovic, Marija. 2008. _The position of Women on the Labor Market in Serbia._ UNDP and Gender Equality Council of the Government of  Serbia, Belgrade

7
# _Calibrating the Model Using Korea Data_

We begin by discussing the debt and threshold rule parameters _bo, fo, do, 0,_ and 'Q. The domestic and foreign debt levels of the public sector in our model were calibrated using the consolidated debt levels of the Korean government and central bank. The Korean Ministry of Finance (MOFE) reports that the level of total government and public sector bonds outstanding at the end of December 1996 was equal to approximately 37.4 trillion won.<sup>15</sup> According to the International Financial Statistics (IFS) of the International Monetary Fund (IMF), the Bank of Korea held claims on the government equal to 2 trillion won as of the end of December 1996. To avoid double counting, we subtracted this number from the reported level of total government and public sector bonds. The IFS also reports that the Bank of Korea had net domestic liabilities (excluding those vis-a-vis the government, official entities and base money) of 4.7 trillion won. Based on this evidence, we conclude that consolidated government domestic liabilities equaled roughly 37.4-2+4.7 = 40.1 trillion won, or 10.3 percent of 1996 GDP. Accordingly we set bo = 0.103.

The Korea Institute for International Economic Policy (KIEP) estimated that the foreign debt of the public sector in June 1997 was equal to 2.0 trillion won.<sup>16</sup> According to the IFS, the value of the central bank's net foreign assets was approximately 28.0 trillion won. This suggests that the overall net foreign assets of the consolidated public sector was equal to roughly 26.0 trillion won or 6.7 percent of 1996 GDP. We set _fo_ = 0.067 and bo _-_ fo = 0.036. According to the Bank of Korea, the value of private sector net foreign debt at the end of 1996 was roughly 13.9 percent of GDP. Accordingly we set do =-0.139.

> '<sup>5</sup> This data was obtained from MOFE's World Wide Web site, http://www.mofe.go.kr/.

> 16The data are published on the Web at http://kiep.go.kr.

17
|**Source**|OECD, IFS, Investing.com<br>OECD, IFS|IFS, BIS<br>BIS, Datastream, FRED<br>FRED<br>FRED<br>FRED<br>FRED<br>FRED<br>FRED<br>OECD<br>IFS, CEPII<br>WDI, WB<br>Chinn-Ito<br>Ghosh, Ostry, Kapan and Qureshi (2015)<br>WDI|CEPII|Bekaert, Engstrom, and Xu (2017)|
|---|---|---|---|---|
||of log real equity equity price indices<br>of log real GDP|of real interest rates<br>of real credit stock<br> Options Exchange (CBOE)<br> U.S. High Yield Spread<br> U.S. Options-Adjusted Spread<br>Corporate Bond Yield<br> Rate<br>nge rate<br>DI<br>private sector as % of GDP<br>Capital account liberalization<br> shares as % of GDP|ude coordinates of country capitals|ncertainty index|
|**Defnition**|The frst diference <br>The frst diference|The frst diference <br>The frts diference <br>The Chicago Board <br>Volatility index<br>BofA Merrill Lynch <br>BofA Merrill Lynch <br>Moody’s Seasoned <br>Real Federal Funds <br>The U.S. real excha<br>Stock of bilateral F<br>Bilateral trade fow<br>Domestic credit to <br>Chinn-Ito index of <br>Exchange rate<br>Total value of listed|es<br>Latitude and longit|Risk aversion and u|
|**le**|returns<br>rowth|t rates<br> growth<br><br> Funds rate<br>ve exchange rate<br>al FDI<br>al trade<br>tic credit<br>ial openness<br>ge rate regime<br>market capitalization|e and longitude coordinat|ersion and uncertainty|
|**b**|y <br> g|s<br>t <br>S<br>Y<br>al<br>i<br>r<br>r<br>s<br>c<br>an<br>|ud|av|
|**ria**|uit<br>P|ere<br>edi<br>X<br>S<br>A<br>CO<br>der<br>ect<br>ate<br>ate<br>me<br>an<br>ch<br>ck|tit|k|
|**Va**|Eq<br>GD|Int<br>Cr<br>VI<br>HY<br>BO<br>M<br>Fe<br>Ef<br>Bil<br>Bil<br>Do<br>Fin<br>Ex<br>Sto|La|Ris|

34
**<u>Annex 3.4: WB Innovative Finance by Country Lending Category, 2000–8 (US$ million)</u>**

|**Lending Category**|**2000**|**2001**|**2002**|**2003**|**2004**|**2005**|**2006**|**2007**|**2008**|**Unspec**|**Total**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Blend|175|125|124|218|110|136|56|15|5|97|1,062|
|IBRD|1,213|1,662|718|591|1,088|705|1,021|857|78|2,252|10,185|
|IDA|662|236|423|652|121|592|760|474|381|841|5,141|
|Other|119|161|243|348|626|787|876|1,465|1,192|1,500|7,317|
|**Total**|**2,169**|**2,184**|**1,509**|**1,809**|**1,944**|**2,220**|**2,713**|**2,810**|**1,656**|**4,690**|**23,704**|

**<u>Annex 3.5: WB Innovative Finance by Corporate</u>**

**Entity and Business Line, FY 2000–8**

|**Business Line**|**Amount (US$ million)**|**Percentage**|
|---|---|---|
|MIGA|8,163<sup>1/</sup>|34.4%<sup>1/</sup>|
|IFC|7,957|33.6%|
|IBRD|3,949|16.7%|
|TF|1,895|8.0%|
|IDA|1,710|7.2%|
|GOVT<sup>2/</sup>|30|0.1%|
|**Total **|**23,704**|**100%**|

**_Note_** _:_<sup>_<u>1/</u>_</sup> _MIGA’s PRI data are not available for FY2008. The percentage has been underestimated. For FY2000–7, MIGA’s innovative finance share is 37.0%._<sup>_2/_</sup> _The GOVT US$30 million (0.1%) belongs to two OBA projects that were funded by “Local Govt.,” as labeled by the OBA team._

**<u>Annex 3.6: Average Annual Flows under WBG Innovative Finance by Use and Objective, 2000–8</u>**

|**Objective and Country Type**|**Avg. US$ per capita**<br>**per annum**|
|---|---|
|**IBRD**|**78**|
|Managingfiscalexposure|1|
|Improving service delivery|23|
|Catalytic|54|
|**IDA and Blend**|**54**|
|Managingfiscalexposure|0|
|Improving service delivery|32|
|Catalyzingmarketdevelopment|23|

45