rafmacalaba/datause-encoder-data huggingface dataset:
These scenarios and corresponding CO2 emission patterns are shown in Figure 9. As expected, there is an order of magnitude decline in CO2 emission from the current situation to the first scenario and then to the second scenario. When all rural households in Bangladesh <!-- Start of picture text --> 100<br>80<br>60<br>40<br>1 2 3 4 5 6 7 8 9 10<br>Income decile<br>Current situation 50% electrification & 50% improved stove use<br>100% electrification & 100% improved stove use<br>CO emission (kg/capita/month)2<br><!-- End of picture text --> Source: BIDS Survey (2004) **Figure 9: CO2 emission in various energy efficiency scenarios by income decile** <!-- Start of picture text --> .8<br>.6<br>.4<br>.2<br>0<br>1 2 3 4 5 6 7 8 9 10<br>Income decile<br>Current situation 50% electrification & 50% improved stove use<br>100% electrification & 100% improved stove use<br>Energy poverty headcount<br><!-- End of picture text --> Source: BIDS Survey (2004) **Figure 10: Energy poverty in different electrification and energy efficiency** <!-- Start of picture text --> .8<br>.6<br>.4<br>.2<br>0<br>1 2 3 4 5 6 7 8 9 10<br>Income decile<br>Current situation 50% electrification & 50% improved stove use<br>100% electrification & 100% improved stove use<br>Consumption poverty headcount<br><!-- End of picture text --> Source: BIDS Survey (2004) **Figure 11: Consumption poverty in various energy efficiency and electrification scenarios by income decile** 34
# **Table** **<u>5: Benefit-Cost Ratios for the Ghana School Feeding Programme</u>**

||Test scores<br>|to labor ea<br>|rnings<br>|Test scores to<br>|years of schoolin<br>earnings<br>|g to labor<br>|
|---|---|---|---|---|---|---|
||All Children<br>(1)|Boys<br>(2)|Girls<br>(3)|All Children<br>(4)|Boys<br>(5)|Girls<br>(6)|
|Annual cost per student, 2017 PPP $|142|142|142|142|142|142|
|Test score effect size, s.d.’s|0.132|0.076|0.205|0.132|0.076|0.205|
|Annual benefit per student, 2017 PPP $|284|163|441|333|191|627|
|(half the two-year treatment effect)|||||||
|Benefit-costratio|2.0|1.2|3.1|<br>2.3|1.3|4.4|

_Note_ : See appendix B for details on the calculations. s.d. = standard deviation. PPP = purchasing power parity. Half the two-year treatment effect: The full treatment includes a two-year intervention and two years of costs. To be comparable to information on costs per year provided in Aurino et al. (2019), we use only half the estimated benefits here.

30
24

## **Table 13: World Total Trade (X+M) and Share in Output by Income Group**

||Wor<br>|ld Trade<br>|(g+s)in$ <br>|billion<br>|Ou<br>|tput(GDP<br>|)in$billi<br>|on<br>|Tota<br>|l Trade<br>|as % of G<br>|DP<br>|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|CountryGroup|1980|1990|2000|2010|1980|1990|2000|2010|1980|1990|2000|2010|
|Developed economies|3,198|6,775|11,275|22,758|8,206|18,329|25,491|42,813|39.0|37.0|44.2|53.2|
|Developing economies|1,094|1,856|4,561|14,108|2,188|3,569|6,700|19,995|50.0|52.0|68.1|70.6|
|High income developing|401|762|1,914|4,693|365|723|1,543|3,057|110.1|105.4|124.1|153.5|
|Upper middle income|437|740|1,935|6,822|1,198|1,935|3,801|12,517|36.5|38.2|50.9|54.5|
|Lower middle income|220|307|642|2,374|542|788|1,212|4,050|40.6|39.0|53.0|58.6|
|Low income|35|47|70|219|83|124|144|370|41.4|37.9|48.7|59.1|
|Of which: LDCs|41|53|93|366|95|143|169|562|43.0|37.1|55.3|65.1|
|World|4,671|8,747|15,989|37,198|11,021|21,977|32,329|63,136|42.4|39.8|49.5|58.9|
|**Memo:**|||||||||||||
|Developing econ, excl.|||||||||||||
|China & India|1,024|1,702|3,905|9,998|1,809|2,886|5,026|12,380|56.6|59.0|77.7|80.8|
|Upper middle income,<br>excl. China|396|636|1,404|3,549|1,008|1,578|2,603|6,587|39.3|40.3|54.0|53.9|
|Lower middle income,<br>excl. India|192|257|516|1,537|352|461|737|2,366|54.4|55.8|70.0|65.0|
|BRICS 5 countries|168|459|1,043|5,563|695|1,774|2,710|11,609|24.2|25.8|38.5|47.9|

Source: World Bank WDI database.

# **POLICY ISSUES**

This strong overall trade performance—with some exceptions, for example Sub-Saharan Africa in manufactures-- raises a lot of questions about the factors responsible, the implications for the architecture of the trading system as well as its sustainability.

How much of this growth was due to the developing countries own policies? To what extent improved market access resulted from the implementation of multilateral trade liberalization following the Uruguay Round Agreements as well as the establishment of numerous regional preferential arrangements? Following the
Empirical work on the effects of job-training for women in developing countries is extremely scarce. For the most part research has been carried out through longitudinal evaluations of government-sponsored training programs in developed countries V. In spite of overall agreement on the main findings of these evaluations, there is a substantial amount of skepticism about their results because the studies used different techniques of analysis and a variety of assumptions to handle the available ronexperimental data (Lalonde 1986). The nonexperimental nature of the data implied that the studies had to make specific assumptions with regard to the procedures used for the "selection" of the participants in the training programs, and for the development of "comparison" groups. Nevertheless, studies agree that jobtraining significantly affects the employment and earnings of women. In fact, it appears that women receive significantly higher returns to training than men, and that most of that difference is associated with the increase in labor supplied by women (Bloom and McLaughlin 1982, Bloom 1987, Bassi et. al. 1984, Boothby 1986). Regardless of the type of program taken, the main effect of training for women is to facilitate labor market entry (Ashenfelter 1978, Kiefer 1979, Westat 1980). The studies indicate that the individuals who were out of the labor force prior to training show the greatest improvement relative to those who had permanent labor force participation. Research also indicates that all types of training programs (classroom, on-the-job, and work internship) noticeably increase the earnings of women, while on-the-job and apprenticeship training programs have the greatest impact on the earnings of men. This difference has been explained by the different training patterns of men and women. Women typically receive skills for clerical and service jobs which can be taught in a variety of institutional settings, while men typically receive skills for blue collar jobs (craftsmen and operatives) which are taught on-the-job or through apprenticeships (Boothby 1986).

**3** These programs seek to provide unemployed, underemployed and economically disadvantaged women with job-skills that will increase their employability and earnings. See, Barnow B., "The Impact of CETA Programs on Earnings: A Review of the Literature", Journal of Human Resources, Spring 1987.

-4-
- **Griliches, Z.** , “Patent Statistics as Economic Indicators: A Survey,” _Journal of Economic Literature_ , 1990, _IV_ , 1661–1707.

- **Grossman, G. and E. Helpman** , “Endogenous Product Cicles,” _Economic Journal_ , 1991, _101_ (408), 1214–1229.

- **and** , _Innovation and Growth in the Global Economy_ , The MIT Press, Cambridge, 1991.

- **Hall, B., J. Hausman, and Z. Griliches** , “Econometric Models for Count Data with an Application to the Patents-R&D Relationship,” _Econometrica_ , 1984, _52_ (4), 909–939.

- **, , and** , “Patents and R&D: Is There a Lag?,” _International Economic Review_ , 1986, _27_ (2), 265–283.

- **Jaffe, A.** , “Technological Opportunity and Spillovers of R&D: Evidence from Firms’ Patents, Profits, and Market Value,” _American Economic Review_ , December 1986, _76_ (5), 984–1001.

- **, M. Trajtenberg, and R. Henderson** , “Geographic Location of Knowledge Spillovers as Evidenced by Patent Citations,” _The Quarterly Journal of Economics_ , 1993, _108(3)_ , 577–598.

- **Javorcik, B.** , “Does Foreign Direct Investment Increase the Productivity of Domestic Firms?. In Search of Spillovers Through Backward Linkages,” _American Economic Review_ , 2004, _94(3)_ , 605–626.

- **Jones, C.** , “R&D-Based Models of Economic Growth,” _Journal of Political Economy_ , 1995, _103_ (4), 759–784.

- **Keller, W.** , “International Technology Diffusion,” _Journal of Economic Literature_ , 2004, _XLII_ , 752–782.

- **Lederman, D.** , “The Business of Product Innovation, International Empirical Evidence,” 2009. Policy Research Working Paper No. 4840.

- **and L. Saenz** , “Innovation and Development Around the World, 1960-2000,” Policy Research

- Working Paper 3774, The World Bank October 2005.

- **MacGarvie, M** , “Do Firms Learn from International Trade?,” _The Review of Economics and Statistics_ , 2006, _88(1)_ , 46–60.

- **Nickell, S.** , “Competition and Corporate Performance,” _Journal of Political Economy_ , 1996, _104_ (4), 724–746.

- **Pakes, A. and Z. Griliches** , “Patents and R&D at the firm level: A first report,” _Economics Letters_ , 1980, _5_ (4), 377–381.

23
imposed on different types of conveyances, which serve to increase the tax rates and their variation across the States.

**Table 2. Stamp Duty Rates on Conveyances in Orissa**

<u>(as percentage tax rate on value of transaction)</u>

|**Value of**<br>**Transaction**|**Rural**<br>**Areas**|**Urban Areas under Town Planning**<br>**and Improvement Trust Act**|**Urban Areas under**<br>**Development Authorities Act**|
|---|---|---|---|
|Rs. 0-2000|6.2|9.2|10.2|
|Rs.2001-5000|7.7|11.2|12.2|
|Rs. 5001-10,000|8.7|13.2|14.2|
|Rs.10,000-25,000|9.7|14.7|15.7|
|AboveRs.25,000|10.7|16.7|17.7|

Source: Tapas K. Sen (1999), “Reform of Stamp Duty Administration in Orissa”, National Institute of Public Finance and Policy (New Delhi, India). Note: In all cases the total stamp <u>duty rate equals the basic rate of 4.2 percent plus an additional charge.</u>

|**Table 3. Maximum St**<br>|**amp Duty Rates on Conveya**<br>|**nces, Selected States**<br>|
|---|---|---|
|**State**|**Maximum Basic Rate**|**Maximum Additional Charges**|
|AndhraPradesh|5.0|--|
|Assam|10.0|--|
|Bihar|7.0|--|
|Bombay|10.0|--|
|Daman|6.0|--|
|Gujarat|8.0|--|
|Himachal Pradesh|12.0|--|
|Karnataka|10.0|4.5|
|Kerala|8.0|--|
|MadhyaPradesh|7.5|--|
|Maharashtra|10.0|--|
|Mizoram|9.0|--|
|Nagaland|5.0|--|
|Orissa|4.2|13.5|
|Pondicherry|9.5|--|
|Punjab|6.25|--|
|TamilNadu|8.0|--|
|Uttar Pradesh|12.5|--|
|West Bengal|5.0|2.0|

Sources: National Institute of Public Finance and Policy (1995), _Economic Reforms and the Stamp Act_ (New Delhi, India); Tapas K. Sen (1999), “Reform of Stamp Duty Administration in Orissa”, National Institute of Public Finance and Policy (New Delhi, India); Government of Karnataka, Finance Department (2001), _1_<sup>_st_</sup> _Report of the Tax Reforms Commission_ (Karnataka, India), and various documents provided by the National Institute <u>of Public Finance and Policy.</u> It is important to note that the stamp duties are directly or indirectly related to a number of other taxes. For example, the value of the transaction affects the individual income tax via the inclusion of short- and long-term capital gains in the income tax. Similarly, valuation affects an individual’s tax liability in the gift tax, as well as in the wealth tax. The property tax in most urban areas is based on the annual rental value of a property. Nevertheless, the annual rental 5
ever there is also a literature looking at firm productivity. The impacts of economic density may be different for firms than for households. Obviously firm productivity directly affects incomes earned, but incomes also reflect labor force participation and matching opportunities for the household, as well as incomes from the informal sector which are not well represented in censuses or typical surveys.

While we found strong neighborhood externalities for different density measures in Table 8, we find no such effects for these types of measures for firms. For firms being in a neighborhood with more people, total employment or Landscan ambient population does nothing to firm productivity measured by value added per worker. The only impact on productivity is from neighborhood localization externalities – having more employment or more firms within a defined neighborhood near a firm within the own industry. And, as we will see even those effects are nuanced, applying to particular sectors and trading off competition versus spillover effects.

# **6.1 Kampala data**

To study firm productivity at the neighborhood level in Kampala, we use data from the Uganda Business Inquiry (UBI) survey conducted in 2002. The UBI is an economic survey which made use of the official Census of Business Establishments (COBE) of 2002 as its sampling frame. The principal objective of the survey is to provide the necessary information and data to measure the contribution of each industry sector to the growth of the economy. So the survey covers a large range of economic variables, including value added and business assets. Coverage is comprehensive, with information on all sectors of the economy - including the informal sector<sup>16</sup> - and coverage of all the officially recognized districts in Uganda. The sector definitions are in line with the International Standard Industrial Classification (ISIC), Revision 4, and cover 15 1-digit sectors.<sup>17</sup> A stratified twostage sample design was used to select the businesses for the UBI, which focused on getting

> 16The informal status of a business is recorded using a question in the survey on whether a business pays any taxes as its determinant; this is in line with other surveys conducted in Uganda such as the UNHS which were more specifically directed to studying informality in the economy.

> 17These are agriculture & fishing, mining & quarrying, manufacturing, construction, utilities, trade, transport & storage, accommodation & food services, information & communication, finance & insurance, real estate & business services, education, health & social work, recreation and personal services. Note that the survey excludes information on the following ISIC sections: Section O, i.e., public administration and defense; compulsory social security, and Section U, i.e., activities of extraterritorial organizations and bodies.

27
**-3-**

# **I.** METHODOLOGY AND DATA

# **1. Methodology**

In this study, we cover all Bank education projects with higher education components from 1972-1992, including formal and non-formal programs leading to a degree, certificate or diploma. The study also covers teacher training projects for which secondary degrees are prerequisites for admittance.

In examining Bank education projects with higher education components, we classified them according to their sensitivity to gender disparity in enrollment rates at the tertiary level and the degree to which the projects introduce specific policy interventions to improve women's access to higher education. Thus, there 're two main categories. The first category includes projects which at the minimum recognized gender as an issue through qualitative analysis of women's participation in post-secondary education and/or identified the constraints associated with low levels of enrollment. These are considered as projects which "acknowledge gender". The second includes projects which go beyond merely recognizing gender as an issue and introduce specific interventions to increase female participation and/or access to higher education. The central focus of the paper is on this second category of projects that contained specific policy interventions aimed at promoting greater gender parity. These projects are analyzed separately and in depth.

# B. Data

Primary resources for this study were World Bank Staff Appraisal Reports (SARs) for higher education projects between 1972 and 1992. For the purpose of analysis, we focused on education projects for which higher education comprised 25% or more of the total project cost. These also included education sector projects and teacher training projects.

For assessing possible shifts in the Bank's approach to gender equity in higher education
**CONFOUNDINC** FINANCIAL **REPRESSION** WITH **RICID URBAN REGULATIONS:**

# **LESSONS OF THE** KORRV. HOUSING KARKET

# **I.** INTRODUCTION

1. The objective of this paper is to explore the interactions between financial and urban policies, and their joint impact on the performance of the housing sector during the course of economic development. The central hypothesis is that extended periods of financial repression and the scarcity of mortgage lending have generated significant distortions in the output of the Korean housing sector. In addition, combined with very restrictive urban planning and land use regulations, this financial situation may have led to under-investment in the urban sector of Korea during much of the past two decades. A broader question which is left unaddressed is whether such distortions and under-investment have been an integral component of the rapid growth policies ol other East Asian market economies such as Japan and Taiwan, or what differences there might be.

2. The original impetus for thinking that financial policies have as much to do with urban outcomes as physical conditions or even income levels came from comparing housing markets operating under different policies and institutions. For instance, why would France which enjoys the largest land area in Europe have higher housing costs and smaller units than Holland which reclaims lar,d from the sea? In Asia, what could be the role of financial policy regimes in two of the most primate cities of Asia: Seoul and Bangkok. During the 1970s and early 1980s both cities were growing rapidly. However, their housing markets were operating in contrasting ways. Seoul had repressive financial policies and skyrocketing real estate values while Bangkok grew rapidly with moderate rises in housing prices under much less interventionist financial policies.

3. Data collected during the preparation of housing projects in Thailand and Korea were showing thit Thai rates of real estate appreciation were quite moderate in spite the rapid demographic growth of Bangkok and significant per capita income gains. As recently reported for Bangkok: "'.asidential land prices as a whole have been increasing in real terms at the moderate rate of 6-10 percent per annum in recent years, faster than incomes. The long-term increases (19711986) appear to have been lower (3 percent percent per annum adjusting for inflation and location). In comparison to 1971, land in land-andhouse and land subdivision projects has now become more affordable", 1/ See PADCO, Bangkok Land Management Study (1988), Executive Summary paragraph 36.
Nadu GP president’s term in office, which is the ninth year of a 10-year reservation cycle).<sup>18</sup> In this case, the DID estimator is given by where _Y_ is the dependent variable of interest (public goods), group _R_ consists of reserved GPs, group _U_ consists of unreserved GPs, and _Y̅g,t_ is the mean value of _Y_ for group _g_ and time _t_ . The DID estimator can also be obtained from a regression of the form for GP _i_ in time period _t_ , where _RESERVED_ is a dummy variable equaling 1 for reserved GPs and _AFTER_ is a dummy variable equaling 1 for observations occurring in 2005, after Tamil Nadu’s reservation policy was implemented. β̂3 is the DID estimate. In a fixed effects estimation—as we perform in Section IV— _RESERVED_ is dropped.

An unbiased estimate of β3 from Equation (2) requires that any unobservable factors that influence whether a GP received treatment and affect the GP’s public goods outcomes have a similar trend over time in reserved and unreserved GPs. For example, if, over time, GPs with higher female population ratios have a different rate of change in political party affiliations and if political party affiliations impact public goods provision, then our estimates could be biased. We provide some evidence of similar trends in reserved and unreserved GPs by comparing the change in village characteristics over 1991–2005 (Table 2, rightmost column). We see no statistically significant difference in the change in village characteristics over the 1991–2005 period for any variables except for the SC population. Although the rate of growth in the SC population was greater in GPs that were unreserved in 2005, we do not think this is a major

> 18 Data on public toilets, household toilets, and buses and minibuses are from 1995 and 2004.  Because 1996 was the first year of reservation, these years are suitable for the analysis, as they provide data from before reservation and from the eighth year of the reservation.

12
23 labour. This Is allowed in those cases where the ejidatarlo cannot take on certain tasks profitably, even though he might dedicate his total efforts to them" (Bartra,1975:143). Such provisions give enormous latitude to federal and local authorities In deciding whether specific instances of renting are permissible; since ejidatarios are generally reokctant to admit to renting (Mummert,1987:532) It would appoar that they thomselves are not convinced that the law will back them up.

38. The restrictlon on renting means that ejido land does not necemarily end up In the hands of those with the means and the vocation to work It. Although, In spite of the law, renting Is currently widespread, It Is reasonable to argue that, In the absence of any ban on leasing, the Incidence of this practice would be even greater: there are presumably a number of ejidatarlos (particularly those on bad terms with the ejldo leadership) who are deterred from renting by the prospect that their parcels may be confiscated. Theoretically, restrictions on leasing would lead to subopthnal use of land, driving down the average productivity of ejidos In reoation to private farms.

39. The situation has been further complicated by the Agricultural Development Law (1981) which seeks to promote "production units" In which ejidos and private producers can jointly produce staple crops (Balley,1981:360); the terms of this arrangement were liberalized by legislation In late 1983, making the contract between ejidatarios and private farmers renewable, not annually as before, but once every three years (Heath,1985:118).

40. While the 1981 Agricultural Census sought to determine the number of these "mixed" (ejido/private) production units, the data (Table 4) probably underestkmate the extent to which ejidatarios and private farmers pool resources. This type of associatlon admits of several possibilities. There are probably many cases where the ejidatarlo supplies his land (and possibly his labour) while the