rafmacalaba/datause-encoder-data huggingface dataset:
Based on recorded wholesale prices for gur, we have extended Kalra's estimates forwards from 1991 and backwards from 1981 by applying a transport cost index to his estimated transport costs in these years, and the general WPI to his estimated processing charges. This gives estimated average cane prices paid by gur producers for the entire 1965-1995 period. In most years, these prices turn out to be considerably lower than the average prices paid by the mills If there were unhindered competition between the mills and the gur producers these prices would be about the same, and any apparent differences would reflect quality, timing and other differences, especially variations in sugar content. However the thrust of regulatory and price controls during the period was on the one hand to protect the mills from competition in buying sugarcane by allotting to each mill protected "catchment areas", and secondly to force the mills to pay above market prices by the use of the annual minimum "state advised prices". Given these policies ,under normal conditions with mill purchases rationed it is plausible that open market purchases of cane are at lower prices for the same or similar cane qualities. On the other hand, in periods of cane scarcity, it is plausible that the gur and khandsari producers can outbid the fixed government-determined prices. These interpretations are consistent with standard accounts of the effects of government policies on cane pricing, especially in UP,<sup>34</sup> and so for the NPC estimates we have assumed that the average quality of the cane used by the gur producers is the same as the average quality of the cane crushed by the mills. Similarly, we have made the additional assumption that the prices paid by khandsari units for cane are the same as the implied prices in gur production. This again seems reasonable since there are no regulatory controls affecting competition for cane as between the khandsari and gur units.

# **Nominal protection of sugar and sugarcane compared**

According to our estimates (see Table 12 and Fig 20) cane has been more protected than sugar in high protection periods i.e. periods of low world sugar prices, and sugar has been slightly more protected than cane (or less disprotected ) than cane during low protection periods i.e when free market world prices have been relatively high. Part of the excess of cane NPCs over sugar NPCs in periods of low world sugar prices is due to the assumption of minimum cane reference prices in some of these years.

Table 12: **NPCs for sugar and cane compared, 1965-94**

|||65-73|74-80|81-87|88-94|65-94|
|---|---|---|---|---|---|---|
|**Importable**|Sugar|2.10|0.80|1.40|0.92|1.36|
||Cane|3.08|0.66|2.13|0.90|1.78|
|**Exportable**|Sugar|3.00|0.94|1.87|1.15|1.82|
||Cane|3.53|0.87|3.11|1.43|2.32|

Source: See Annexes 1, 3, 14 and 15.

34 See for example Harrison, Hitchings and Wall (October 1981) or the _Indian Sugar Yearbook._ 47
**POLIcy RESEARCH WORKING PAPER** 3103

# Abstract

Aggarwal and Klapper study the relationship between ownership structure, corporate governance, and the initial public offering (IPO) process. They examine equity ownership by different institutions, such as foreign and domestic financial institutions, banks with and without lending relationships, venture capitalists, and corporations prior to an IPO. The authors also analyze the relationship between ownership structure and corporate governance. They use a unique dataset of 152 Indian IPOs during the period 1999-2001 to analyze ownership of shares by main groups of shareholders. The authors find a relationship between ownership structure and firm-specific factors such as sales, leverage, and profitability, and IPO characteristics such as percentage of equity locked up, gross proceeds, and exchange of listing. There is also a strong relationship between ownership by different types of institutions. Ownership is also tied to bank lending relationships. Finally, the authors find strong relationships between ownership types and corporate governance. For example, firms with foreign investors are more likely to have an outside chief executive officer and offer an employee stock option plan.

This paper-a product of Finance, Development Research Group-is part of a larger effort in the group to study international corporate governance. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Agnes Yaptenco, room MC3-446, telephone 202-473-1823, fax 202-522-1155, email address ayaptenco@worldbank.org. Policy Research Working Papers are also posted on the Web at http:// econ.worldbank.org. The authors may be contacted at aggarwal@georgetown.edu or Iklapper@worldbank.org.<sup>July 2003.</sup> (27 pages)

> _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objectiveof the series is toget thefindingsoutquickly, even if the presentationsare less than fuilly polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent._

Produced by Partnerships, Capacity Building, and Outreach
about 300 million are learning English. Even in India, foreign professionals, ranging from pilots to surveyors, are increasingly filling the gap between the needs of dynamic domestic industries and the dysfunctional higher education system.

Figure 1: Total Emigration from Five EU Countries Worst Affected by the Crisis, 2002-2011 <!-- Start of picture text --> 600,000<br>500,000<br>400,000 Ireland<br>Greece<br>300,000<br>Spain<br>200,000<br>Italy<br>100,000 Portugal<br>0<br><!-- End of picture text --> Source: Underlying data is drawn from Eurostat, http://appsso.eurostat.ec.europa.eu Figure 2: Total Emigration from Spain by Region of Next Residence, 2011 (percentage of total emigration) <!-- Start of picture text --> 8%<br>10% EU<br>33%<br>Latin America<br>Africa<br>17%<br>Asia<br>Other<br>32%<br><!-- End of picture text --> Source: Underlying data is drawn from Eurostat, http://appsso.eurostat.ec.europa.eu 8
variations in poverty in terms of changes in _per capita_ expenditure and changes in inequality.

In section 3 we apply a novel approach to counterfactual decomposition of outcome distributions (Fortin, Lemieux and Firpo 2010; Firpo, Fortin and Lemieux 2009 a&b). In particular, using recentered influence function (RIF) regressions, the approach allows us to link the relevant growth incidence curve to house characteristics and to perform Oaxaca-Blinder type decomposition across quantiles. This way we can tell whether different factors (such as the distribution of characteristics or the returns to those characteristics) have different impacts at different points of the outcome distribution. We also use the same methodology to decompose the rural-urban gap in the distribution of economic welfare. For policymaking purposes, we need to understand the nature of the changes in the distribution of welfare associated with the process of economic growth. While the Shapley decomposition limits this understanding to changes in mean welfare and inequality, the generalized Oaxaca-Blinder decomposition allows a much richer analysis (Bourguignon and Ferreira 2005, Fortin, Lemieux and Firpo 2010)<sup>6</sup> . However, both methods base the identification of the determinants of differences across distributions of economic welfare on the comparison of _counterfactual distributions_ with observed ones. Concluding remarks are made in section 4.

# **2.  A Profile of Growth, Inequality and Poverty**

In this section, we present a summary of the three datasets we use in the analysis. We also discuss the observed poverty outcomes and try to link them to changes in per capita expenditure and inequality.

Table 2.1. Distribution of Per Adult Equivalent Annual Expenditure in Cameroon (1996-2007)

||Mean|Lowest<br>Decile|2nd|3rd|4<sup>th</sup>|5<sup>th</sup>|6th|7th|8th|9th|10th|
|---|---|---|---|---|---|---|---|---|---|---|---|
|1996|243262.2|2.89|3.78|4.88|6.66|7.26|8.04|7.99|10.45|13.94|34.10|
|2001|372742.6|2.64|4.00|5.19|6.79|6.67|8.59|10.07|11.56|15.59|28.90|
|2007|432894.2|2.70|3.95|4.74|6.22|7.74|9.30|10.65|12.87|16.64|25.19|

Source: Authors’ Calculations (using data from the 1996, 2001 and 2007 household surveys)

> 6 Within this framework outcome differentials are explained in terms of individual (or household) endowments (or characteristics) and the returns to those assets.

5
16 unemployment rate stands at 25.1 percent for women living in poor households against 19.5 percent for women from non poor families. Yet, the gender gap does not increase with poverty: female unemployment rate amounts to roughly double of that of males whether they belong to poor or non poor households.

_Differentials between the poor and the non poor narrow to some extent with education, but the poor with some schooling exhibit significant unemployment rates_ (Figure 7) _._ Unemployment among the poor with no schooling is roughly twice as high as that observed for the non poor (16.6 percent compared to 8.7 percent). The gap between the poor and the non poor with some schooling is somewhat smaller: 24.3 percent of the poor with primary education and 26.3 percent of those with secondary education are unemployed compared to 18.1 percent and 20.1 percent respectively for the non poor.

_The gap observed in unemployment between rural and urban areas is mainly due to the non poor._ Indeed, similar proportions of the poor and extremely poor report being unemployed in rural and urban areas. However, for the non poor, the difference widens: 10.2 percent of the rural non poor are jobless compared to 14.6 percent of the urban non poor.

**Table 7. Unemployment Rate by Poverty Status, Gender, Living Area, and Age Group (in %)**

||_All_|_Non Poor_|_Poor_|_Extremely Poor_|
|---|---|---|---|---|
|_All_|14.7|12.6|17.2|19.8|
|_By gender:_|||||
|_Male_|11.4|9.8|13.5|15.2|
|_Female_|22.3|19.5|25.1|29.4|
|_By living area:_|||||
|_Rural_|14.2|10.2|17.2|20|
|_Urban_|15.3|14.6|17.3|19.4|
|_By age group:_|||||
|_15-24_|33.8|30|37.1|42.8|
|_25-54_|9.6|9.1|10.3|11.6|
|_55-64_|1.9|1.8|2|2.1|

Source: EPCV 2004. Figures are displayed in percentage.

_Finally, correlation between poverty and unemployment is starker for the 15 to 24 age group._ As shown in Table 7, while 37.1 percent of the young from poor households and 42.8 percent of those from extremely poor families report being unemployed, this figure stands at 30 percent for the non poor. In contrast, other age groups display similar unemployment rates across wealth groups.
Policy ReseaRch WoRking PaPeR 4660

# **Abstract**

Asymmetric auctions are among the most rapidly growing areas in the auction literature. The potential benefits from improved auction efficiency are expected to be enormous in public procurement auctions related to official development projects. Entrant bidders are considered a key to enhance competition in an auction and break potential collusive arrangements among incumbent bidders. Asymmetric auction theory predicts that weak (fringe) bidders would bid more aggressively when they are faced with a strong (incumbent) opponent. Using official development assistance procurement data, this paper finds that in the major infrastructure sectors, entrants submitted systematically aggressive bids in the presence of an incumbent bidder. The findings also show that a high concentration of incumbents in an auction would harm auction efficiency, raising procurement costs. The results suggest that auctioneers should encourage fringe bidders to actively participate in the bidding process while maintaining the quality of the projects. This is conducive to enhancing competitive circumstances in public procurements and improving allocative efficiency.

This paper—a product of the Economics Unit, Finance, Economics and Urban Development Department—is part of a larger effort in the department to understand and investigate efficiency and effectiveness in public infrastructure procurement. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at aiimi@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
<!-- Start of picture text --> &, |<br><!-- End of picture text -->

<!-- Start of picture text -->
1.0 e<br>o<br>$09 o*<br>3 . e .<br><<br>os‘ oe ° a‘ bg<br>3 e<br>0.7<br>a °. °<br>ro ° e e<br>| 0.6 : bd<br>(@} °°<br>e<br>0 100 200 300 400 500 600 700 800<br>Number of plots<br><!-- End of picture text -->

<!-- Start of picture text --> °<br>0.6<br>Oo<br>Ss e<br>€ ° p| * °<br>2 0.4 "<br>0.2 .<br>¢ e . °<br>6= 0.0 —« ° ° ad id. BS<br>+ | e<br>ar Yor e e<br>0 100 200 300 400 500 600 700 800<br>Number of plots<br><!-- End of picture text -->
**Table 3 Impact of migration on sending household’s welfare**

|VARIABLES|(1)|(2)|(3)|
|---|---|---|---|
|male_head|-0.0236|-0.0391|-0.0867***|
|age_head|-0.0153***|-0.0114***|-0.0105**|
|age_head<sup>2</sup>|7.53e-05|5.24e-05|6.39e-05|
|prim_head|-0.0356|-0.00302|-0.0236|
|seci_head|0.120***|0.134***|0.157***|
|secc_head|0.443***|0.436***|0.451***|
|terc_head|0.699***|0.720***|0.750***|
|married_head|0.0443|0.0409|0.0569*|
|hhsize|-0.0593***|-0.0591***|-0.0592***|
|dep_child|-0.450***|-0.360***|-0.354***|
|ownhouse|0.107***|0.122***|0.116***|
|ownfarm|-0.228***|-0.201***|-0.182***|
|selfemp|0.130***|0.144***|0.156***|
|urb|0.322***|0.300***|0.280***|
|lland|0.00774***|0.00917***|0.00905***|
|Western|0.0403|0.131*|0.150*|
|Central|-0.0235|0.0444|0.156**|
|Volta|-0.170*|-0.115|-0.0647|
|Eastern|0.0605|0.166**|0.185***|
|Ashanti|-0.0280|0.00881|0.103|
|Brong_Ahafo|-0.103|-0.0424|-0.0304|
|Northern|-0.165*|-0.117|-0.121|
|Upper_East|-0.496***|-0.520***|-0.549***|
|Upper_West|-0.876***|-0.708***|-0.777***|
|mstatus|0.708***|||
|migrurb||0.622***||
|migrrur|||0.252|
|ρ|-0.6096***|-0.5518***|-0.1997|
|Observations|3700|3700|3700|

*** p<0.01, ** p<0.05, * p<0.1.

_Note_ : Observations are weighted by sample weights and standard errors are clustered at the PSU level. Stratification at the region level is also taken into account in the estimates. Only the second stage estimates are shown; migration rate at the district level is the identifying variable in the first stage. The table reports untransformed value of ρ , although hypothesis testing was done on its inverse hyperbolic tangent ( α tanh ρ).

18
Table 2. Treatment Effects on Prosocial Behavior Toward Venezuelan Forced Migrants

||Donation to<br>Venezuelan<br>Org. [=1]|Donation to<br>Non Migrant<br>Org. [=1]|Trust|Prosociality<br>Index|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|_Panel A. Treatment Effects_|||||
|Game [=1]|0.106***|0.027|0.297***|0.267***|
||(0.037)|(0.034)|(0.080)|(0.080)|
||[0.008]|[0.264]|[0.002]||
|Video [=1]|0.111***|0.038|0.116|0.201**|
||(0.039)|(0.035)|(0.090)|(0.089)|
||[0.008]|[0.207]|[0.178]||
|Observations|828|828|828|828|
|Av. Dep. Var. (Control grp.)|0.667|0.781|0.000|0.000|
|Diff. p-value|0.879|0.752|0.033|0.430|
|YWYjoint test|0.009|0.440|0.001||
|_Panel B. Treatment Effects by D_|_uration in Minut_|_es_|||
|Game Duration|0.003***|0.001|0.010***|0.009***|
||(0.001)|(0.001)|(0.003)|(0.003)|
||[0.007]|[0.217]|[0.001]||
|Video Duration|0.016***|0.006|0.017|0.030**|
||(0.006)|(0.005)|(0.014)|(0.014)|
||[0.009]|[0.197]|[0.193]||
|Observations|828|828|828|828|
|R-squared|0.016|0.006|0.019|0.017|
|Av. Dep. Var. (Control grp.)|0.667|0.781|0.000|0.000|
|Diff. p-value|0.016|0.322|0.608|0.097|
|YWYjoint test|0.003|0.432|0.001||

_Notes:_ This table presents the estimates from an OLS estimate derived from Equation 1. The dependent variables, (i) Donation to Venezuelan Org. and (ii) Donation to Nonmigrant Org., are indicator variables measured by an incentivized dictator game in which participants decide whether to donate money to an organization that supports Venezuelan migrants’ access to health, education, and legal advice, and/or to an organization that supports vulnerable populations in Colombia, respectively. (iii) Trust is the z-scored variable from a four-point scale ranging from 1 (strongly disagree) to 4 (strongly agree) on the statement, “One can trust Venezuelan migrants.” (iv) The Prosociality Index is constructed using the dependent variables of columns (1) to (3), employing the methodology outlined by Kling, Liebman and Katz (2007). This method involves standardizing each variable within the index, calculating the average, and standardizing this average using the mean of the control group. All columns control for gender and student status, the stratification variables. Robust standard errors are reported in parentheses, and False Discovery Rate (FDR) q-values are reported in brackets. Av. Dep. Var. (Control group) represents the mean of the dependent variable in the control group. The Diff. p-value is a Wald test of equality of coefficients between the game treatment and video treatment. YWY denotes the sharpened FDR q-values. Significance levels are indicated as<sup>_∗∗∗_</sup> at 1%,<sup>_∗∗_</sup> at 5%,<sup>_∗_</sup> at 10%.
- 49 -

would be very high because of their low capital cost (this is confirmed by the Singapore evidence) and, provided that the geographical conditions are not insurmountable, these schemes would appeal to local transport authorities facing hard budget constraints. The pracal ERP Schemes possess revenue-cost ratios that range from 8 to 10, whereas the theoretical optimum ERP option yields the revenue-cost ratio of 19- the highest of all the measures considered.

64. With the 1989 Green Paper on Transport Policy, the Hong Kong Government again tested public opinion on electronic road priing under the guise of 'area prcing'. It turns out that the Second Comprehensive Transport Study (CTS-2), wbich forms the basis of the consultative Green Paper, shows that area pricing is in fact ERP Scheme B resurrected (Transport Department and Wilbur Smith and Associates, 1989, Figure 9.3 and Table 9.5)." A slightly lower charge (two thirds) of the original 1985 ERP Scheme B proposal was simulated. The CTS-2 concludes that area pricing is technicaUy the best means of combatting congeston in selected areas. Dogged by continuing concerns about the potential intrmuion of privacy by 'big brother' and accentuated by the issue of 1997 (when Hong Kong will be rened to China), the Hong Kong Government revealed in the ensuing White Paper of 1990 that it has decided to retain area pricing by electronic devices as a long-term option and to monitor the technological developments and their applications elsewhere. In early 1992, the Govemment bepn testing state-of-the-art automatic vehicle identificon technology using the Amtech one-way radio ftequency-based and the PREMID stored value, two-way radio commations systems for electronic toll collecdon at the Aberdeen and Cross Harbour Tunnels. Since April 1992, a pilot project has been operating at the Aberdeen Tunnel on Hong Kong Island, with futl commercial operation expected in April 1993 pending legislative changes to the tunnel ordinances and bylaws. Given Hong Kong's previous exeience, the publicly owned but privately operated tunnel companies have offered their clients full protection from invasion of privacy through the estabLishment of numbered account arangements. If either of the AVI technologie is adopted, Area pricing is a vadrt of BRP Scdm B boomu it extends the charging days to includo Saturdy (inc Hong Kong does operate an a aix-day work week). Hce all do above alyui an HRP applies mod i quite timey. Th eferec yar is chged from 1991 to 1996.
**Table 19: Annual value added per worker (in million LCU) in presumed comparative advantage industries by size group of enterprises (weighted estimates of totals  at 2000 prices)**

**(weighted estimates of totals  at 2000 prices) , UBI 2002 and UBI 2009‐**

# **_A. All comparative advantage_**

|**_industries_**|||**_E. Comm_**|**_ercialfarming_**|
|---|---|---|---|---|
|**Size Group**|Annual va<br>worker|lue added per|Annual valu<br>worker|e added per|
|**(number of workers)**|2002|2009|2002|2009|
|less than 5|1.9|6.3|1.8|4.0|
|5‐20 workers|4.4|41.5|3.1|2.8|
|21‐100 workers|12.5|22.5|1.4|10.8|
|More than 100|7.5|14.6|1.5|7.6|
|Total|7.0|18.7|1.6|5.2|
|**_B. Comparative advanta_**|**_geprimary indus_**|**_tries_**|**_F. Food_**|**_and beverages industry_**|
|**Size Group**|Annual va<br>worker|lue added per|Annual valu<br>worker|e added per|
|**(number of workers)**|2002|2009|2002|2009|
|less than 5|1.9|2.8|1.8|12.4|
|5‐20 workers|3.0|3.1|4.1|32.1|
|21‐100 workers|1.4|9.1|18.8|20.5|
|More than 100|1.5|7.5|8.8|15.9|
|Total|1.6|4.6|8.2|17.9|
|**_C. Comparative advantage man_**|**_ufacturing indust_**<br>l|**_ries_**<br>l|**G. Th**<br>l l|**egarments industry**<br>|
|**Size Group**|Annua va<br>worker|ue added per|Annua va<br>worker|e added per|
|**(number of workers)**|2002|2009|2002|2009|
|less than 5|1.6|7.4|1.3|5.4|
|5‐20 workers|4.0|30.4|1.5|28.9|
|21‐100 workers|19.2|29.1|0.6|4.0|
|More than 100|9.6|16.1||0.2|
|Total|8.3|16.3|1.3|8.1|
|**_D. Comparative advant_**|**_age services_**||**H. Land tr**|**ansport services**|
|**Size Group**|Annual va<br>worker|lue added per|Annual valu<br>worker|e added per|
|**(number of workers)**|2002|2009|2002|2009|
|less than 5|7.8|8.2|8.9|5.0|
|5‐20 workers|14.3|548.2|14.8|11.6|
|21‐100 workers|7.4|21.1|7.4|18.1|
|More than 100|31.8|5.8|13.4|5.8|
|Total|26.6|184.7|12.4|13.0|

55