rafmacalaba/datause-encoder-data huggingface dataset:
42 Shah, A. T. Thompson and H.F. Zhou (2004), “The Impact of Decentralization on Service Delivery, Corruption, Fiscal Management and Growth in Developing and Emerging Market Economies: A Synthesis of Empirical Evidence”, _CESifo Dice Report_ 2: pp.10-14 Reinikka, R. and J. Svensson (2002), “Coping with poor public capital”, _Journal of Development Economics,_ 69 (1), pp51-69 Shapiro, C and R. Willig (1990), “Economic rationale for the scope for privatization”, in E.N. Suleiman and J. Waterbury (eds), **The political economy of public sector reform** , Westview Press Shleifer, A. and R. Vishny (1994), “Corruption”, _Quarterly Journal of Economics,_ 109, pp995-1025 Svensson, J. (2003), “Who must pay bribes and how much? Evidence from a cross section of firms”, _Quarterly Journal of Economics_ , Vol. CXVIII, February, 208-230 Rock, M.T. and H. Bonnett (2004), “The comparative politics of corruption: Accounting for the East Asian paradox in empirical studies of corruption, growth and investment”, World Development, 32(6), pp999-1017 Rossi, M. and E. Del Bo (2004), “Corruption and Inefficiency: Theory and Cross-Country Evidence from Electricity Distribution Firms ”, in Rossi, M (2004), **Essays in Applied Regulatory Economics** , PhD thesis, University of Oxford, available at ~ <u>http://users.ox.ac.uk/ rossi/Paper%202.pdf</u> Tanzi, V. andH. Davoodi (1997), Corruption, Public Investment and Growth”, IMF Working Paper, No 97/139, available at http://www.imf.org/external/pubs/ft/wp/wp97139.pdf wb14570 N:\Antonio\tena2\povnet \survey of infrastructure issues - WP version.doc September 29, 2004 10:31 AM
percentage points (from 70 to 80 percent) for the basic education age group, and close to 12 percentage points (from 46 to 58 percent) for the secondary school age group. While the most advantaged group of children accumulate on average one year of education for each year from age 6 onwards all the way up to age 22 (reaching 15.2 years of educational attainment), in the least advantaged group, educational attainment remains less than 7 years on average.

**Figure 8:  The enrollment and educational attainment gap between least and most advantaged circumstance groups is large, but narrowed in the 2000s.**

<!-- Start of picture text --> Enrollment by Age Level Educational Attainment by Age Level<br>(indicates lower enrollment and early drop-out) (indicates lower total educational attainment)<br>6 8 10 12 14 16 18 20 22 6 8 10 12 14 16 18 20 22<br>Age Age<br>Least advantaged group Most advantaged group Least advantaged group Most advantaged group<br>Source data: Egypt DHS 2000 (sample of children ages 6-22) Source data: Egypt DHS 2000 (sample of children ages 6-22)<br>Enrollment by Age Level Educational Attainment by Age Level<br>(indicates lower enrollment and early drop-out) (indicates lower total educational attainment)<br>6 8 10 12 Age14 16 18 20 22 6 8 10 12 Age14 16 18 20 22<br>Least advantaged group Most advantaged group Least advantaged group Most advantaged group<br>Source data: Egypt DHS 2008 (sample of children ages 6-22) Source data: Egypt DHS 2008 (sample of children ages 6-22)<br>1 15<br>.8<br>10<br>.6<br>.4<br>Enrollment Rate 5<br>.2 Educational Attainment<br>0 0<br>1 15<br>.8<br>.6 10<br>.4<br>Enrollment Rate 5<br>.2 Educational Attainment<br>0 0<br><!-- End of picture text -->

# **5. Inequality of Opportunity in Access to Basic Services**

This section presents the measures of inequality of opportunity in access to basic services among Egyptian children. As described in Section 3, inequality of opportunity is defined as inequality in access to basic services due to differences in circumstances beyond children’s control. While Section 4 looked at the availability of and access to these services and its trends during the 2000s, 22
2 International migration is one of the most important factors affecting economic relations between developed and developing countries in the 21<sup>st</sup> Century. At the start of the century the United Nations estimated that about 175 million people – roughly 3 percent of the world population – lived and worked outside the country of their birth. The remittances – money and goods – sent back home by these migrant workers have a profound impact on the living standards of people in the developing countries of Asia, Africa, Latin America and the Middle East. In 2002 the flow of international remittances to developing countries stood at $80 billion per year, a figure which was much higher than total official aid flows to the developing world.<sup>1</sup> The purpose of this paper is to examine the impact of international migration and remittances on poverty in a broad cross-section of developing countries. In the past, a number of studies have examined the effect of international migration and remittances on poverty in specific village or country settings,<sup>2</sup> but we are not aware of any studies which examine the impact of these phenomena on poverty in a broad range of developing countries. Two factors seem to be responsible. The first is a lack of poverty data; it is quite difficult to estimate accurate and meaningful poverty headcounts in a wide and diverse range of developing countries. The second factor relates to the nature of data on international migration and remittances. Not only do few developing countries publish records on migration flows, but many developed countries which do keep records on migration tend to undercount the large number of illegal migrants living within their
2004 ) show a great deal of fluctuation, with a clear break between crisis and non-crisis periods (Figures 2 and 3).Thus interacting US interest rate variables with variables which capture the severity of the debt problem may be essential to capturing the effect of global monetary conditions on emerging market spreads.

**Figure 2. Correlation of EMBI and US interest rates rolling three-year periods.  Dec 1995-Aug 2004**

<!-- Start of picture text --> 1<br>0.8<br>fedrate<br>0.6<br>gs10<br>0.4<br>0.2<br>0<br>-0.2<br>-0.4<br>-0.6<br>-0.8<br>Figure 3 Correlation of EMBI and US interest rates rolling<br>three-year periods Dec 1995-Aug 2004<br>1<br>0.8 fedrate<br>0.6<br>0.4 tb3m<br>0.2<br>0<br>-0.2<br>-0.4<br>-0.6<br>-0.8<br>-1<br>Dec-95Jun-96Dec-96Jun-97Dec-97Jun-98Dec-98Jun-99Dec-99Jun-00Dec-00Jun-01Dec-01Jun-02Dec-02Jun-03Dec-03Jun-04<br>Dec-95Apr-96Aug-96Dec-96Apr-97Aug-97Dec-97Apr-98Aug-98Dec-98Apr-99Aug-99Dec-99Apr-00Aug-00Dec-00Apr-01Aug-01Dec-01Apr-02Aug-02Dec-02Apr-03Aug-03Dec-03Apr-04Aug-04<br><!-- End of picture text -->

**Figure 3 Correlation of EMBI and US interest rates rolling three-year periods Dec 1995-Aug 2004**

Second, the possibility of multiple equilibria should be taken into account. We see this possibility as being related to changes in global liquidity conditions and the 9
1 17 concluded that enforcement of job security laws has been detrimental to labor mobility in both countries, permitting labor costs in manufacturing to increase. In the case of Mexico, Riveros (1988a,b) found that job securLty laws present a major difficulty in carrying out an industrial adjustment based on opening up the economy and exchange rate realignment. Reform in this area in Chile during the 1970s **was** considered crucial by entrepreneurs facing a more competitive environment associated vith substantial trade reforms (Corbo 1985). For Zambia, Colclough (1988) reports the existence of a demadning set of regulations enforced by **the** governmont, while Riveroc (1987), Collier & Riveros (1987), Collier & Lal (1986) and Collier (1988) suggest the same type of problem **ar*** prevalent in the Philippines, Nigeria, Kenya and Tanzania, respectively. Likewise, Pollack (1988) argues that these regulations **are** predominantly enforced in most Latin American countries.

By examining the Price-Waterhouse reports on prevailing job security regulations in the countries covered in this study, a ranking can be produced with regard to the obligations of employers when dismissing workers.<sup>13</sup> According to this, Korea, Singapore, Hong Kong and Nigeria rank among the countries with lesser requirements. On the other hand, Argentina, ColombLa, Mexico, Kenya, India, Greece and Portugal, are, among those where job security regulations are extremely stringent. By contrasting these results with those in Tables 1 and 2, there seema to be a very high correlation between the existence of relatively high NWC ratios and coercive job security laws. As comonly stated in Price Waterhouse's reports, compliance wLth the law is guaranteed through several controls imposed by the political authorities **as** well **as** by union activities. Thus, it is a reasonable hypothesis that NWC regulations are also significantly enforced in the countries studied. 1 4
10 in the districts of Anuradhapura and Vavuniya show correlations of 0.4 to 0.7 between tank storage level and rainfall on a monthly basis. The tank storage levels also show the general trend of the rainy seasons. For example, monthly average storage levels from the Nuwara Wewa tank in Anuradhapura show that storage levels increase with the rains starting in November-December, peak in January, and stay stable until June before sharply declining over July to October<sup>21</sup> due to the lack of rain during these months. Tank water levels are managed by the relevant institutions (Refer Box 1) to ensure sufficient water supply to farmers via the irrigation network. Historical tank storage data in million cubic meters (MCM) for the 11 major tanks in Anuradhapura district are shown in Figure 1.<sup>22</sup>

**Figure 1. Historical Tank Effective Storage (MCM) for Major Tanks in Anuradhapura District**

<!-- Start of picture text --> 120.00<br>100.00<br>80.00<br>60.00<br>40.00<br>20.00<br>0.00<br>Abaya Wewa Huruluwewa Mahakandarawa Mahawilachchiya<br>Manankattiya Nachchaduwa Nuwara Wewa Padaviya<br>Rajangana Tisa Wewa Wahalkada<br>Oct-11 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14 Jan-15 Apr-15 Jul-15 Oct-15 Jan-16 Apr-16 Jul-16 Oct-16 Jan-17 Apr-17 Jul-17 Oct-17 Jan-18 Apr-18<br><!-- End of picture text --> Source: Author-constructed based on MCM data from Irrigation Department of Sri Lanka.

While rainfall and water available for irrigation are positively correlated as expected, their correlation is not all that high due to other factors that affect the water tank level – such as inflows from canals and tanks in other regions. This implies that rainfall on its own cannot be a very good proxy of tank storage level, and thereby the water available for irrigation.

The other important aspect is the correlation between tank storage levels and crop yields/losses. Data from three Yala seasons in Vavuniya showed a strong negative correlation of -0.93 between the

> 21 Irrigation Department, Ministry of Irrigation and Water Resources Management, Sri Lanka.

> 22 Irrigation Department, Ministry of Irrigation and Water Resources Management, Sri Lanka.
# **5.2 Notes on Interpretation**

In the following section, we report urban trend results for September 2014 – December 2021 and dummy-variable results for two five-year periods: January 2015 – December 2019 and January 2017 – December 2021. Before presenting the results, we believe that some interpretive notes are warranted. First, we offer a caveat about viewing long- and short-period differences across urban areas as indicators of differential performance, because “performance” implies intentionality on the part of public or private actors. However, even highly-significant changes in local concentration anomalies may reflect non-intentional factors such as changed agricultural practices, blight-induced forest degradation, or additional emissions from traffic congestion during periods when mass transit systems are installed. Measurement anomalies may also intrude, particularly for model (7) because it focuses on relatively short-run changes.<sup>10</sup> To summarize, it may be more useful to view tracking results as guides to detailed local assessments rather than as performance indicators.

A note about measurement units is also warranted. In Dasgupta, Lall and Wheeler (2022), we convert concentration anomalies to emissions estimates using the overall ratio of total global CO2 emissions (drawn from standard sources) to the total for all grid squares of concentration anomalies predicted from the parameters of our econometric model. This enables us to perform a distribution of predicted CO2 emissions across all terrestrial cells of the 25 km global grid. However, we have little confidence in our current ability to infer changes in emissions volumes from directly-observed changes in local anomalies that are not linked to identifiable ground sources. For this reason, our trend estimation exercise operates solely with concentration anomalies. This has no practical consequence, since the results provide readily-comparable change estimates.

# **5.3 Tracking Data**

We estimate models (6) and (7) for 1,799 functional urban areas (FUAs) whose data provide at least 30 degrees of freedom for estimation.<sup>11</sup> Table 4 enumerates the outlying observations that are removed prior to estimation. Observations with standardized z-values greater than 5.0 have been identified as outliers.<sup>12</sup> As the table shows, 1,761 of 1,799 FUAs have no outliers. Single outliers have been removed for 35 FUAs, 2 outliers for 2 FUAs and 3 for 1 FUA.

> 10 See particularly Weir et al. (2021) for a useful discussion of potential effects from year-to-year variability caused by differences in atmospheric circulation.  We address this issue in Section 5.5. 11 The sample is much larger than the sample used in Section 4 because models (6) and (7) do not absorb degrees of freedom with dummy variable controls for grid cells.

> 12 The z-value of an observation is its distance from the mean, measured in standard deviations.

12
# **Distributional Effects of WTO Agricultural Reforms in Rich and Poor Countries**

_“Trade theory is about whose hand is in whose pocket and trade policy is about who should take it out.”_ Finger (1980) This paper is about some well-known hands in well-known pockets but in new combinations and at a level of detail that has not previously been possible. For the first time it considers the trade-offs in global agricultural trade reform between farmers in rich and poor countries making use of farm-level and household-level data. It delves further into the distributional consequences of reform than previous research and in doing so lays bare some of the political economy that has made agricultural trade reform so tortured.

The Doha Development Agenda (DDA) of the World Trade Organization (WTO), which is currently suspended, has an explicit mandate to improve welfare and reduce poverty in developing countries (WTO, 2004). The bulk of the global gains from merchandise trade reform derive from reforms in agriculture (Hertel and Keeney, 2006; Anderson and Martin, 2006), and most of these are predicted to accrue to rich countries as they reduce outlays on farm programs and reduce protection for agricultural products. But such reforms also benefit many households in developing countries – particularly those in the farm and rural sectors, which comprise a majority of the world’s poor – so it would seem that such reforms should be an easy sell to policy makers in rich and poor countries alike. Experience suggests the opposite, for the failure to agree on a package of agricultural liberalizations was the principal cause of the suspension of talks in mid-2006.
men, being in the same state increases migration between neighboring districts by about 149 percent ( _e_<sup>1</sup><sup>_._852</sup><sup>_−_0</sup><sup>_._939</sup> _−_ 1) as seen in column 4.

Table 8 splits the population by reason for migration, revealing large differences between men and women. As mentioned earlier, women migrate predominantly for marriage reasons to nearby districts while men migrate for employment reasons to more distant areas. As a result, distance is a large impediment for women migrating for marriage (column 5) relative to other reasons. The importance of distance for women migrating for marriage appears again in the neighborhood coefficients, which are significantly higher for this group. For men migrating for work, common language and being neighbors seem to be less important (column 2). The negative state border effect for males is significant for migration motivated by movement with the family, work and education, but not marriage.

# **4.2 Robustness checks**

The labor mobility between two districts could depend on the _relative_ level of attributes such as income levels, extent of urbanization or literacy rates, in addition to distance, contiguity and linguistic overlap. To account for this possibility, we include several relative “attraction” metrics as controls. Using 2001 census tables and 2004 National Sample Survey (NSS) data, we calculate the following variables at the district level: (i) the percentage of non ST/SC population,<sup>16</sup> (ii) the literacy rate, (iii) the urbanization rate, (iv) the share of private employment in the labor force, (v) the share of formal employment in the labor force, and (vi) average income. Districts with higher values of these metrics are likely to attract more migrants from districts with lower values. The attraction between an origin district _i_ and destination district _j_ due to an attribute _a_ is then measured by _s_<sup>_a_</sup> _ij_<sup>=</sup><sup>_a_</sup> _a_<sup>_<u>j</u>_</sup> _i_<sup>.Sincethesebilateralvariables</sup> are correlated across district-pairs, we do not insert them separately into the regression. Instead, we calculate the overall “attraction index” between _i_ and _j_ which is a

> 16“ST/SC” refers to “scheduled tribes and scheduled castes.”

19
- p=p(a(ePNPP) PP+(l-a)(ePNPP)XP) P-(WPP+raP)NPP wP'NP' =*max, The term, _rae,_ gives any start-up costs associated with the provision of social benefits that might face de novo firms. We can imagine that such costs might be non-trivial particularly in a context where there is a poorly functioning real estate market. The first order conditions for the maximization problem are;

pF'(-)ax(eP)'"(NPP)-PP=- **_wPP_** _+raP_ pF'(.)a(eP)-P(NPs)-PP-' _wPs_ With the CES fumction, we get the allocation of employment, as follows; Obviously, the number of workers of each type is determined by the ratio of compensation to effort (when s > 1). The degree of such dependence is proportional to the elasticity of substitution. If the elasticity of substitution is equal to 1 there is no explicit dependence in the allocation of employment on the ratio of efforts (although there exists an implicit dependence on effort through the coefficients a and 1-a). The sensitivity in the allocation of labour to differences in wages, benefits, start-up costs and effort increases in step with the elasticity of substitution between the two types of labour. We should also notice that we have an implicit constraint on the number of full time workers which should be at least greater than, or equal to, one. A smaller value for the number of full time workers implies a corner solution. These are possible under two scenarios. The first arises if the effort exerted by full time workers is much greater than the eff6rt exerted by part-time workers and the second if the start-up costs associated with providing social benefits are large.

# **Withdrawing subsidies: effects on compensation and employment**

We have indicated that in a system where workers in state or privatised firms get compensated with a mix of cash wages and benefits and where outside provision of such benefits is restricted or where potential providers face large start-up costs, there will be a strong tendency for de novo firms to rely on part-time labour and hence for 11
19

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