rafmacalaba/datause-encoder-data huggingface dataset:
|||(0.520)||(0.556)|
|---|---|---|---|---|
|Very high risk||0.070||-0.187|
|||(0.578)||(0.627)|
|**Experienced flooding on business premises**: Yes|||-0.559|-0.744*|
||||(0.340)|(0.400)|
|Log (electricity usage, kWh/month)|0.661***|0.650***|0.676***|0.681***|
||(0.111)|(0.115)|(0.111)|(0.115)|
|Log (electricity costs, $/kWh)|0.305**|0.313**|0.343**|0.315**|
||(0.142)|(0.144)|(0.141)|(0.147)|
|Firm age (years)|0.012|0.014|0.015|0.015|
||(0.011)|(0.011)|(0.011)|(0.011)|
|Number of employees|0.002|0.002|0.003|0.002|
||(0.004)|(0.004)|(0.004)|(0.004)|
|Log (total operational costs, $/month)|0.204**|0.196**|0.171*|0.188*|
||(0.095)|(0.096)|(0.095)|(0.100)|
|**Time until firm needs to halt production without**|||||
|<br>**electricity**(no halt)|||||
|Less than 6 hours|-0.167|-0.193|-0.203|-0.194|
||(0.400)|(0.395)|(0.383)|(0.402)|
|More than 6 hours|-0.408|-0.359|-0.353|-0.344|
||(0.438)|(0.440)|(0.427)|(0.440)|
|Immediate|0.747**|0.776**|0.750**|0.696*|
||(0.344)|(0.357)|(0.346)|(0.365)|
|**Time since last serious disaster**(<2 months)|||||
|2–12 months|1.071|1.033|1.145|0.998|
||(0.781)|(0.749)|(0.760)|(0.813)|
|> 12 months|0.574|0.556|0.657|0.475|
||(0.750)|(0.717)|(0.720)|(0.793)|
|**Region**(Dar es Salaam)|||||
|Dodoma|-0.464|-0.474|-0.410|-0.815|
||(0.528)|(0.508)|(0.544)|(0.543)|
|Tanga|-0.981***|-0.871**|-0.991***|-1.038***|
||(0.364)|(0.362)|(0.362)|(0.386)|
|**Sector**(Accommodation and food service|||||
|<br>activities, Construction):|||||
|Communication and other services|-0.405|-0.445|-0.525|-0.373|
||(0.410)|(0.422)|(0.406)|(0.417)|
|Manufacturing, Mining, Water, Energy,|||||
|<br>Agriculture|-1.927***|-1.943***|-2.012***|-1.932***|
||(0.452)|(0.465)|(0.474)|(0.451)|
|Transportation and storage|0.130|0.067|0.125|0.187|
||(0.694)|(0.736)|(0.696)|(0.748)|
|Wholesale and retail trade Repair of motor|||||
|,<br>vehicles and motorcycles|-0.982**|-1.034***|-1.079***|-1.028***|
||(0.381)|(0.394)|(0.390)|(0.378)|
|Constant|-5.230***|-4.994***|-5.080***|-4.892***|
||(1.006)|(0.969)|(0.975)|(1.038)|
|Observations|606|606|604|604|

_Note:_ All coefficients refer to the linear predictor in a logistic regression model. Effects cannot be interpreted as a linear effect on probabilities but state the effect on log odds ratios. Reference levels of categorical variables in parentheses. Standard errors are clustered on the ward level in parentheses: *** p<0.01 ** p<0.05 * p<0.1 44
# **1. Introduction**

A large literature from poverty reduction to behavioral economics has documented that development outcomes vary across social groups. Research on gender-based disparities, for example, shows that there are significant gaps between men and women in a wide range of outcomes, including earnings, human capital endowments, health, education and other labor market outcomes (e.g. World Bank 2011a). Recently, welfare patterns related to other social divisions have received attention as well, with studies indicating large differences across race, ethnicity, caste and religious groups (e.g. Hall and Patrinos 2012, Das 2008, Das and Dutta 2008). As the link between different identities and outcomes are becoming clearer, more complex questions arise: Do individuals and groups disadvantaged on the basis of one of their identities face additional barriers because of the way their identities interact with each other? Do these barriers result in cumulative disadvantages, indicating and/or contributing to exclusion of certain groups from society?

As a concept, _intersectionality_ has made important contributions to gender analysis by prompting discussions about how to understand and analyze gender in combination with other identities. The intersectional approach seeks to understand individuals’ and groups’ positions within multiple systems of “interlocking oppressions” (Collins 1999) and how the intersection of multiple identities affect their wellbeing, experiences and social structures (Phoenix and Pattynama 2006). The feminist literature highlights, for example, that day-to-day experiences of ethnic minority women are drastically different from ethnic majority women, although both groups fare worse than men in most outcomes. While what makes ethnicity exacerbate genderbased divisions (and vice versa) often requires a detailed understanding of the context in which these relationships take place (Anthias 2012), existing data sources can help identify if the intersection of gender and ethnicity is associated with systematic welfare disparities across groups. The presence of such gaps can point to cumulative disadvantages that exclude individuals and groups who possess multiple identities from certain outcomes.

2
given the income. Banks in some large countries like Mexico and Colombia offer limited mortgage financing, but when considering a wider set of LAC countries, mortgage lending compares favorably to peers. Lower commercial and consumer credit underlines the problems of access to finance for micro, small, and medium enterprises that abound in LAC. The smaller firms, largely informal, frequently use consumer loans to fund working capital needs. This finding is corroborated by the Enterprise Surveys, which show that small and medium firms in LAC cite finance as a major obstacle to doing business, and the corresponding numbers for the world, especially East Asia and the Pacific (EAP) and ECA, for small- and medium-size firms are much lower.<sup>26</sup> We also found that the relationship between credit by maturity and purpose is nonlinear. In low-income countries, short-term credit grows faster than long-term credit as income grows but the situation reverses when countries reach upper-middle-income status. Consumer lending grows faster with income in low-income countries. As countries develop, commercial loan growth accelerates while mortgage growth accelerates only when countries reach high-income status.

The results of the simple correlation analysis conducted in this paper are consistent with previous findings. Long-term credit is associated with sound macroeconomic frameworks, higher income levels, higher savings mobilization, and good financial infrastructure and legal frameworks. Regarding bank ownership, the negative association between credit levels and foreign banks found in the literature seems to be driven by medium- and short-term credit. On the other hand, the negative association between public (government) bank ownership and credit levels seems to be driven by long-term credit (over five years). Focusing on LAC, patterns of association are similar to other countries in other developing regions except in the case of depth of credit information.

While these results are suggestive, additional work is necessary to properly identify patterns of association and causality effects between macroeconomic and financial variables and long-term credit around the world and in LAC. Bayesian Model Averaging (BMA) and Generalto-specific (Gets) approaches can be used in a cross-country framework to address missing variable bias. A cross-country panel data introducing country dummies could also be used provided there

> 26 Enterprise Surveys 2018.

20
Policy Research Working Paper 9335

# **Abstract**

This study developed a land cover and land use mapping framework specifically designed for agricultural systems in the Sudan-Sahel region. The mapping approach extracts information from inter- and intra-annual vegetation dynamics from dense stacks of Landsat 8 images. The framework was applied to create a 30-meter spatial resolution land use map focusing on the 2015 agricultural landscapes in northern Nigeria. The map provides up-todate information with a high level of spatial and thematic detail, resulting in a more precise characterization of agriculture in the region. The map reveals that agriculture is the main land use in the region. Arable land represents on average 52.5 percent of the area, which is higher than the reported national average for Nigeria (38.4 percent). Irrigated agriculture covers nearly 2.2 percent of the total area, reaching nearly 20 percent of the cultivated land when traditional floodplain agriculture systems are included, which is above the reported national average (0.63 percent). There is significant variability in land use in the region. This study demonstrates the feasibility of multitemporal medium-resolution remote sensing data to provide detailed, up-to-date information on agricultural systems in the arid and sub-arid landscapes of the Sahel region.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at vmolini@worldbank.org or mazad@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
# **III. Antidumping and Safeguard Investigations and Their Final Determinations (1987-2003)**

## **1. Requests, Initiations, and Types of Investigations**

Between 1987 and 2003, the Mexican government initiated 262 investigations, of which 92% were caused by dumping practices and 7% by subsidies, while only 1% of the cases initiated until December 2003 were caused by safeguard measures<sup>45</sup> (Table 3 below). These data only take into account initiations of new investigations and exclude proceedings derived from original investigations, such as reviews of final determinations or sunset reviews. Proceedings are quantified by product-country pairs following the WTO criterion, i.e. a resolution to initiate an investigation on corrugated rods against imports from Brazil and Spain is taken as two investigations. The only exception to the rule is the so-called “China Package”.

**Table 3 - Antidumping, Anti-Subsidy, and Safeguard Proceedings Initiated in Mexico, 1987 - 2003**

|**Type of**<br>**investigation**|**Number of**<br>**investigations**|**Percentage vis-**<br>**à-vis the total**<br>**number of**<br>**investigations**|**Number of**<br>**concluded**<br>**cases**|**Number of**<br>**concluded cases**<br>**with measures in**<br>**force in 2002**|**Percentage of**<br>**concluded cases,**<br>**with measures**<br>**currently in effect**|
|---|---|---|---|---|---|
|Dumping|240|91.6%|216|74|34.26%|
|Subsidies|19|7.2%|18|7|38.89%|
|Safeguards|3|1.1%|3|1|33.33%|
|Total|262|100.00%|237|82|34.18%|

Source: UPCI and 2003 DOF data.

According to the information available, 73% of the requests for investigation filed are admitted by the competent authority.<sup>46</sup> Eighty-six percent of the investigations initiated lead to the application of provisional duties, while 58% concluded with the imposition of antidumping or countervailing duties. These percentages have apparently increased with the passing of

> 45 The statistical annex includes a detailed list of all the investigations initiated in that period.

> 46 This percentage corresponds to the 1992-2002 period, of which records of rejections are available. Prior to that date, any request rejected by the authority on the grounds of non-compliance with formalities or irrelevance was notified to the interested party only.

16
Aker, J.C., 2011. Dial “A” for agriculture: a review of information and communication technologies for agricultural extension in developing countries, _Agricultural Economics_ , 42(6): 631-647.

Almlund, M., A. Duckworth, J. J. Heckman, and T. Kautz (2011). Personality psychology and economics. In E. A. Hanushek, S. Machin, and L. W ̈oßmann (Eds.), _Handbook of the Economics of Education_ , Volume 4, pp. 1–181. Amsterdam: Elsevier.

Barrick, M. R. and M. K. Mount, 1991, The Big Five personality dimensions and job performance: A meta-analysis, _Personnel Psychology_ 44 (1), 1–26.

Beard, T. R., Ford, G. S., Saba, R. P., & Seals, R. A., 2012, Internet Use and Job Search. _Telecommunications Policy_ , 36(4), 260-273.

Becker, G., 1962, Investment in human capital: A theoretical analysis, _Journal of Political Economy_ 70 (9).

Burga, P. I. R. and M. E. G. Barreto, 2014, The effect of Internet and cell phones on employment and agricultural production in rural villages in Peru, Manuscript, Harris School of Public Policy, University of Chicago.

Duckworth, A.L., C. Peterson, M.D. Matthews, D.R. Kelly, 2007, Grit: Perseverance and passion for long-term goals, _Journal of Personality and Social Psychology_ , 92 (6), pp. 1087-1101.

Heckman, J.J. and T. Kautz, 2012, Hard evidence on soft skills, _Labour Economics_ , 19 (4), August 2012 Heckman, J. J. and S. Mosso, 2014, The economics of human development and social mobility. _Annual Review of Economics_ 6 (1), 689–733.

Hogan, J. and B. Holland, 2003, Using theory to evaluate personality and job-performance relations: A socioanalytic perspective. _Journal of Applied Psychology_ 88 (1), 100–112.

John, Naumann and Soto, 2008, Paradigm shift to the integrative Big Five trait taxonomy: History, measurement and conceptual issues, Chapter4, In O. P. John, R. W. Robins, & L. A. Pervin eds., _Handbook of personality: Theory and research_ , New York, NY: Guilford Press.

Kautz, T., J.J. Heckman, R. Diris, B. Weel, and L. Borghans, (2014), Fostering and measuring skills: Improving cognitive and non-cognitive skills to promote lifetime success, NBER Working Paper 20749 Klonner, S., & Nolen, P. J., 2010, Cell Phones and Rural Labor Markets: Evidence from South Africa. Proceedings of the German Development Economics Conference, Hannover 2010 56, Verein für Socialpolitik, Research Committee Development Economics.

Kroft, K., & Pope, D. G., 2014, Does Online Search Crowd out Traditional Search and Improve Matching Efficiency? Evidence from Craigslist, _Journal of Labor Economics_ , 32(2), 259-303.

15
|(mean = 0.23)<br>(5)<br>0.028<br>(0.005)**<br>-0.064<br>(0.005)**<br>-0.061<br>(0.012)**<br>0.032<br>(0.004)**<br>-0.025<br>(0.006)**<br>-0.111<br>(0.030)**<br>0.026<br>(0.029)<br>59118<br>4745<br>tion with these<br>tandard errors<br>unicipality and<br>s of per capita<br>tate or federal<br>ndicates p_<_.01;<br> of average per<br>ni coefcient is|
|---|
|n municipal pre-primary school <br>(3)<br>(4)<br>0.030<br>0.027<br>(0.005)**<br>(0.006)**<br>-0.018<br>(0.002)**<br>-0.051<br>-0.054<br>(0.011)**<br>(0.012)**<br>-0.007<br>0.226<br>(0.005)<br>(0.022)**<br>-0.015<br>-0.008<br>(0.007)*<br>(0.006)<br>-0.048<br>-0.050<br>(0.023)*<br>(0.030)+<br>-0.033<br>-0.038<br>(0.036)<br>(0.034)<br>59118<br>59118<br>4745<br>4745<br>ent for revenue and its interac<br>h the same covariates. Robust s<br>el. All specifcations include m<br> with the pre-reform, 1997 level<br>ic primary school students in s<br>rimary enrollment squared. ** i<br>apita revenue is 9.61, the mean <br> income is 0.22, and the mean Gi<br>INEP, and Tesouro Nacional.|
|Dependent Variable: Fraction of 0-6 population enrolled i<br>(1)<br>(2)<br>Revenue<br>0.004<br>0.003<br>(0.002)+<br>(0.002)<br>Revenue x average income<br>-0.017<br>(0.002)**<br>Revenue x median income<br>-0.057<br>(0.005)**<br>Revenue x gini<br>Average income<br>0.213<br>0.033<br>(0.022)**<br>(0.004)**<br>Population<br>-0.018<br>-0.034<br>(0.007)**<br>(0.009)**<br>0-6 population<br>-0.070<br>-0.126<br>(0.029)*<br>(0.030)**<br>7-15 population<br>-0.003<br>0.057<br>(0.031)<br>(0.032)+<br>Observations<br>59154<br>59154<br>Municipalities<br>4748<br>4748<br>_Notes:_ An observation is a municipality - year. I instrum<br>covariates using simulated revenue and its interaction wit<br>are in parentheses, and clustered at the municipality lev<br>year fxed efects, as well as a linear time trend interacted<br>revenue, per capita transfer revenue, the fraction of publ<br>(non-municipal) schools, pre-primary enrollment, and pre-p<br>* indicates p_<_.05; + indicates p_<_.10. The mean of per c<br>capita income is 0.64, the mean of 2000 median per capita <br>0.39. Population is measured in 100,000s.<br>_Sources:_ Author’s calculations based on data from IBGE,|

46
- 2 -

# **I. INTRODUCTION**

In recent years it has become increasingly important to understand the demand for electricity, because of highly volatile international energy prices and global warming expected in the future. How to manage the consumer demand for electricity remains a challenge for many developing and transition economies. To this end, metering is essential, because it is generally difficult to design an effective tariff structure without sufficient meters installed. Lack of metering also complicates other governance issues, such as electricity theft, and generates a significant adverse effect on the sector’s financial viability and the country’s energy security and growth.

This paper examines the residential electricity demand in Albania, using micro data from the country’s household surveys. Particularly, it casts light on the potential impacts of metering and climatic conditions. To estimate the unbiased demand function, several important econometric issues need to be addressed, such as simultaneity between price and quantity, self-selection of metering, and partially observable electricity consumption. By using a twostage method, the paper will show that metering is an important determinant of the residential demand for electricity. It will also show that higher-than-usual temperature and increasing ownership of air conditioners would likely push up the electricity demand in Albania.

Metering is a fundamental step for successful utilities to promote energy efficiency and financial sustainability. This may be intuitively obvious, but it is not as simple as it looks. For instance, the U.K. experience indicates that metering per se may not always be required for the utility service provision. In the United Kingdom, historically, only about one-third of domestic water users are metered. Hence, if the capacity of supply is sufficient and the demand is well predicted even in the absence of meters, utilities may not have to install meters. But this is very difficult in practice.<sup>1</sup>

> 1 In the United Kingdom, water services have not been charged based on metering until recently. Given the 2005 drought and severe water shortage, water supply companies embarked upon the metering program. By legislation, water companies in areas of serious water stress will be able to compulsorily meter customers from
become more educated, the cohort-specific random effect drops and turns negative (though insignificant) at the 1976 cohort. The youngest cohort is an exception, as despite the strong reduction in women who never went to school the cohort-effect on fertility is smaller than for the two previous cohorts (though it stays strongly significant and negative). From Figure 2, it seems obvious that the rising levels of education have contributed to the drop in fertility in Rwanda.

Residual variation in fertility by period is statistically significant but small in comparison to cohort variation (standard deviation of _0.116_ for period compared to _0.461_ for cohorts). This suggests that the social and economic changes observed between 2005 and 2010 did contribute to driving down fertility but were substantially less important than the cohort effects.<sup>13</sup> In sum, the results presented in Table 3 suggest that the decline in fertility is predominantly due to cohort effects, with younger cohorts systematically having fewer children than the cohorts before, controlling for age of women and time period of the surveys.<sup>14</sup>

# **Statistical Decompositions**

Table 4 examines the drivers of the fertility decline between 2005 and 2010 using the Oaxaca-Blinder decomposition specified in equation (4). The decompositions are based on cross sectional regressions for both the 2005 and the 2010 survey. For reasons of space the regressions are not presented but are available on request. The conditional correlations estimated by both regressions are qualitatively similar: women’s education and participation in the labor force, household wealth scores, and women’s exposure to mass media are negatively related to fertility, and education of the household head (most often the husband) and age of the woman are positively associated with fertility. Women without exposure to mass media have on average lower fertility, though this is likely due to selection effects.

> 13 Using longer (10-year) or shorter (3-year) cohorts instead of the standard 5-year cohorts does not change the results.

> 14 In contrast, the fertility declines in the US, Europe and South Korea can largely be explained by period effects (Pullum, 1985; Foster, 1990; Kye, 2012). These studies however span a far greater time period than the five years examined in this paper.

18
# **TABLE 19 Foreign Direct Investment By Country of Origin** (Percent Composition)

|Year|USA|UK|Germany|Japan|Switzerland|France|Spain|Sweden|Canada|Others|
|---|---|---|---|---|---|---|---|---|---|---|
|1980|66.47|3.00|10.53|7.59|6.87|1.20|4.93|0.67|1.08|-2.33|
|1981|63.02|2.40|8.60|12.47|4.40|0.61|5.98|0.90|0.31|1.31|
|1982|68.01|1.18|6.37|10.44|3.69|1.09|6.45|-0.32|1.29|1.80|
|1983|38.99|7.20|16.09|0.56|2.37|16.09|1.86|4.26|3.23|9.36|
|1984|63.79|3.10|10.67|2.49|4.18|0.61|0.82|4.27|2.27|7.81|
|1985|76.74|3.26|3.21|4.59|8.17|0.62|0.81|0.32|2.02|0.28|
|1986|49.76|4.30|9.01|5.87|1.41|13.07|3.87|1.01|1.67|10.02|
|1987|68.85|11.11|1.21|3.43|2.46|0.80|3.24|0.95|0.50|7.45|
|1988|39.33|24.31|4.33|4.71|2.73|4.83|1.08|1.03|1.07|16.57|
|1989|72.56|1.79|3.39|0.63|7.78|0.66|1.76|0.28|1.50|9.66|
|1990|62.00|3.07|7.74|3.25|3.98|4.86|0.28|0.36|1.50|12.96|
|1991|66.94|2.08|2.38|2.06|1.92|14.04|1.23|0.39|2.08|6.88|
|1992|45.89|11.86|2.36|2.41|8.76|1.92|1.03|0.06|2.46|23.26|
|1993|71.49|3.86|2.27|1.50|2.08|1.57|1.30|0.05|1.51|14.37|
|1994|45.98|5.66|2.91|6.01|0.51|0.86|1.38|0.09|7.06|29.54|
|1995|65.19|2.64|6.79|1.93|2.48|1.48|0.52|0.76|2.09|16.13|
|1996|67.15|1.01|2.62|1.88|1.03|1.61|0.81|1.31|6.52|16.07|
|1997|59.84|17.06|4.33|3.17|0.27|0.55|2.44|0.07|1.88|10.40|
|1998|70.54|2.45|2.91|1.89|0.23|1.06|2.54|0.21|2.76|15.41|

Data from 1980-93 and 1994-98 are not strictly comparable due to a change in the methodology. SOURCE: INEGI 50