rafmacalaba/datause-encoder-data huggingface dataset:
Also, one should select the values for the key normative parameter related to mortality. Our results reveal the importance of establishing what is the plausible range of values for the normative weight given to mortality. Again, preference elicitation methods should provide a sense of this range.<sup>22</sup> θθ

# **REFERENCES**

Alkire, Sabina, et al. _Multidimensional poverty measurement and analysis_ . Oxford University Press, USA, 2015.

Alkire, Sabina, and James Foster. "Counting and multidimensional poverty measurement." _Journal of public economics_ 95.7-8 (2011): 476-487.

Baland, Jean-Marie, Guilhem Cassan, and Benoit Decerf. "" Too Young to Die": Deprivation Measures Combining Poverty and Premature Mortality." _American Economic Journal: Applied Economics_ 13.4 (2021): 226-57.

Baland, Jean-Marie, Guilhem Cassan, and Benoit Decerf. "Poverty-Adjusted Life Expectancy." (2022).

Battiston, Diego, et al. "Income and beyond: Multidimensional poverty in six Latin American countries." _Social indicators research_ 112 (2013): 291-314.

Becker, Gary S., Tomas J. Philipson, and Rodrigo R. Soares. "The quantity and quality of life and the evolution of world inequality." _American economic review_ 95.1 (2005): 277-291.

- - Bolch, Kimberly, Luis F. Lopez Calva, and Eduardo Ortiz Juarez. "“When Life Gives You Lemons”: Using Cross - Sectional Surveys to Identify Chronic Poverty in the Absence of Panel Data." _Review of Income and Wealth_ (2022).

Chukwuonye, Innocent Ijezie, et al. "Prevalence of overweight and obesity in adult Nigerians–a systematic review." _Diabetes, metabolic syndrome and obesity: targets and therapy_ (2013): 43-47.

Decerf, Benoit. "Why not consider that being absolutely poor is worse than being only relatively poor?." _Journal of Public Economics_ 152 (2017): 79-92.

Decerf, Benoit. "A preference-based theory unifying monetary and non-monetary poverty measurement." _Journal of Public Economics_ 222 (2023): 104898.

Decerf, Benoit, and Mery Ferrando. "Unambiguous trends combining absolute and relative income poverty: new results and global application." _The World Bank Economic Review_ 36.3 (2022): 605-628.

<mark>Evans, Martin, Ricardo Nogales, and Matthew Robson. "Monetary and Multidimensional Poverty: Correlation, Mismatches, and a Combined Approach."</mark> _<mark>The Journal of Development Studies</mark>_ <mark>(2023): 1-24.</mark> Fleurbaey, Marc. "Beyond GDP: The quest for a measure of social welfare." _Journal of Economic literature_ 47.4 (2009): 1029-1075.

Hicks, Norman, and Paul Streeten. "Indicators of development: The search for a basic needs yardstick." _World development_ 7.6 (1979): 567-580.

33
a4ln(W1it)*ln(W2it) + a5ln(W1it)*ln(W3it) + d1Trend + d2Trend<sup>2</sup> + d3Trend*ln(Qit)+d4Trend*ln(W1it ) + d5Trend*ln(W2it ) + where i denotes banks and t denotes years. C is total operating plus financial costs, Q is total assets, W1 is the ratio of interest expenses to total deposits and money market funding (proxy for input price of deposits), W2 is the ratio of personnel expenses to total assets (proxy for input price of labor) and W3 is the ratio of other operating and administrative expenses to total assets (proxy for input price of equipment/fixed capital). We also include a trend to capture the influence of technical change leading to shifts in the cost function over time. As in most papers, the estimation is done under the restrictions of symmetry and degree one homogeneity in the price of inputs. However, our results do not change if we drop these constraints.

The Lerner Index for Jordan indicates rising market power among banks in the system over most of the period 1994-2006 (see Figure 3). According to data from Bankscope, the Lerner index has risen steadily from 0.14 to 0.41 (or 41%) between 1994 and 2006. This decline in competition is consistent with what we find using the H-statistic. Relative to measures reported for other countries such as Mexico and the European Union (EU) (see Maudos and Solis, 2007 for Mexico and Fernandez de Guevara et al., 2005 and 2007 for the EU), the current numbers for Jordan seem to indicate greater evidence of market power, and hence a lower degree of competition.<sup>8</sup>

# **6. Conclusions**

The banking sector in Jordan is concentrated. However, the link between concentration and competition is not always clear. Hence, an analysis of competition in the banking sector requires a broader framework. This paper proposes a framework for analyzing competition which

> 8 Maudos and Solis find that the Lerner Index for Mexico varied between 0.05 and 0.15 between 1993 and 2005. Fernandez de Guevara, Maudos and Perez (2007) find estimates of the Lerner Index for the EU between 0.13 and 0.15, depending of the year considered between 1993 and 2000.

- 10 -
**Appendix D - Computer Penetration as an Additional Covariate**<sup>**19**</sup>

||**Column 1**|**Column 2**|**Column 3**|**Column 4**|
|---|---|---|---|---|
||**Aggregate**<br>**Paper**|<br>**Newsprint**|**Printing**<br>**and**<br>**Writing**|**Household**<br>**and**<br>**Sanitary**|
|Internet|||||
|Pentration (per<br>100 people)|-0.00405**|-0.00536*|-0.00701**|-0.00471|
||(0.0020)|(0.0028)|(0.0033)|(0.0047)|
|Computer||-|||
|Pentration (per<br>100 people)|-0.00474**|0.00928**<br>*|-0.00539|0.00168|
||(0.0022)|(0.0032)|(0.0037)|(0.0053)|
|GDP per capita (in<br>logarithm)|<br>1.238***|0.438|1.692***|2.845***|
||(0.2790)|(0.4160)|(0.4680)|(0.6740)|
|Percentage Post|||||
|High School<br>Students (over<br>whole population)|1.478|13.69**|9.52|-8.39|
||(4.0900)|(6.0270)|(6.9800)|(10.1400)|
|Workers in|||||
|Primary Sector<br>(percentage)|-2.358|0.226|0.172|7.112|
||(2.1630)|(3.1660)|(3.6490)|(5.0860)|
|Workers in|||||
|Manufacturing<br>Sector|-0.422|-4.786|-0.916|6.708|
|(percentage)|||||
||(2.1370)|(3.1280)|(3.5740)|(4.8870)|
|Workers in the<br>Services<br>(percentage)|-1.709|3.147|-4.943|2.445|
||(2.1340)|(3.1850)|(3.6570)|(4.7760)|
|Constant|-5.877|-3.222|-10.15|-29.11***|
||(3.8650)|(5.7770)|(6.5440)|(9.1870)|
|Observations|352|347|323|265|
|R-squared|0.98|0.967|0.957|0.947|

19 The collection of these indicators has been discontinued due to difficulties in measuring them adequately. Methodological criteria for the selection of ICT indicators for country and regional factsheets ITU 31
# **4. Recent climate change in Chile**

In this section we will analyze climate data for Chile from May 1948 to March 2008 to test whether there are any significant trends, and whether these trends differ between regions.

We will use the Monthly Climatic Data for the World database collected by the National Climatic Data Center (NCDC) in the US. This project started in May 1948 with 100 selected stations spread across the World, including five in Chile. Since then, many more stations have been included in the data base, but only seven stations in Chile have contributed systematically throughout the period, with only inconsequential gaps. These are listed in Table 5, ordered from north to south.

**Table 5: Meteorological stations in Chile with almost** **<u>complete monthly data, 1948-2008</u>**

|**Station**|**Latitude**|**Longitude**|**Elevation**<br>**(m)**|
|---|---|---|---|
|Arica|18°21'S|70°20'W|55|
|Antofagasta|23°26'S|70°27'W|140|
|La Serena|29°55'S|71°12'W|146|
|Isla Juan Fernandez|33°37'S|78°49'W|30|
|Valdivia|39°38'S|73°05'W|43|
|Puerto Montt|41°26'S|73°06'W|110|
|PuntaArenas|53°00'S|70°51'W|90|

_Source:_ NCDC’s Monthly Climatic Data for the World.

The original data was organized in 61 printed volumes with 12 issues in each (one for each month of the year), totaling 719 months. All data has been quality-checked and was published by the NCDC about three months after the raw data had been collected. From each of these monthly issues, we extracted average monthly temperature and total monthly precipitation for the seven Chilean stations listed above, in order to create time series for each station.

Once the temperature and precipitation series had been constructed and checked for unrealistic values (there was only one, which was eliminated), we proceeded to calculate “normal” temperatures and “normal” precipitation for each station-month for the reference period 1960-90.

Table 6 shows the average “normal” values for temperature and precipitation for each month for each of these stations. It is seen that the climate differs dramatically from region to region, with Arica and Antofagasta being located in tropical desert climates with almost no rain, while Valdivia and Puerto Montt are located in temperate, wet climates. There is also a sub-tropical island, Isla Juan Fernandez, with mild temperatures and moderate amounts of rain, and Punta Arenas with very cold winters, due to the location far south.

10
# **<u>Figure 1:</u>**

## Internet Diffusion in Different Countries

<!-- Start of picture text --> 70<br>60<br>50<br>Brazil<br>China<br>40<br>France<br>India<br>30 South Africa<br>Tanzania<br>United States<br>20<br>10<br>0<br>1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004<br>Year<br>Percentage of Users<br><!-- End of picture text --> Source: ITU dataset In the second part of the paper we identify candidates to explain the different crosscountry patterns in Internet diffusion. Our most important finding is the presence of network effects in Internet diffusion: the number of Internet users in the previous year is a powerful determinant of the number of Internet users in the current year. The presence of network effects as a determinant of Internet adoption has been largely ignored in existing literature<sup>4</sup> , a striking fact considering that the utility derived from Internet consumption is affected by the number of people using it (Shy, 2001). In addition, we study two determinants that have not been accounted for in the literature: the competition in the market for the provision of Internet services and the role of language. Controlling for different relevant variables, we find that in countries where there is more competition in the distribution of Internet, the number of users increases more rapidly. Sharing a common language has a positive impact on the spread of Internet use.

The paper is organized as follows. Section 2 briefly summarizes the existing theoretical and empirical literature on technology diffusion and, in particular, on Internet diffusion. Section 3 describes the main dataset used throughout the paper. The empirical estimation of Internet diffusion curves is presented in Section 4. In Section 5 we explore the determinants of Internet diffusion across countries. Finally, Section 6 concludes the paper.

> 4 Estache _et al._ (2002) is an exception as these authors included a lagged variable of Internet users but found it not significant as determinant of Internet adoption.

3
drinking water and roads in West Bengal and drinking water in Rajasthan (women collect drinking water in both places, and are employed building roads in West Bengal). They invest relatively less in public goods that are linked to men's concerns: education in West Bengal and roads in Rajasthan. In a follow-up study, Beaman et al. (2006) analyze how these different policies affect children. They provide evidence from two Indian states that children in villages headed by female leaders have higher immunization rates and that girls experience an improvement in school attendance.

# **2.6  Direct Evidence on Preference Differences**

One potential explanation for the observed differences in spending patterns is that women and men have different preferences. Croson and Gneezy (2009) provide an overview of the experimental evidence on gender differences in preferences. They conclude that there is robust evidence that women are more risk averse than men. They also document gender differences in other-regarding preferences such as altruism, inequality aversion, and reciprocity. However, women are not generally more other-regarding than men. It is not clear how these preference differences affect parents' attitudes towards children.

Bauer and Chylitová (2009) specifically examine how gender differences in preferences depend on the presence of children. They measure the discount rate and risk aversion using data from lab experiments in rural India. They find evidence of gender differences in the discount rate, but not in attitudes toward risk. Interestingly, childless men and women turn out to have the same discount rates, but women with children under 18 are more patient than men with children. The more children the women have, the more patient they are relative to men with the same number of children.

A different kind of evidence on gender differences in preferences is provided by Woolley (2004). The paper surveys a small sample of couples with children in Ottawa, Canada, to study gender differences in spending. People were asked in interviews how they spend their child benefits and what they would do with unexpected additional income. The study finds that women are more likely to say that they would spend a windfall on children and household goods, while men are more likely to say they would spend the money on savings. However, the difference is statistically insignificant.

9
36 -

-

# FOOTNOTES

- 1 These statements assume a population of 4,830,900 in 1975 and 6,465,100 in 1984 (projected on the basis of information given in Table 1), together with levels of formal employment, for those years, indicated by Table 4.

- 2 The declining trend indicated by Table 4 for the years 1964-72 relates to non-Africans, as itdicated in the notes to the Table. Although their numbers fell consistently, there was a rising tide of non-Zambian African inrAigrants from elsewhere in the continent. As is suggested by the data which use a changed basis of classification from 1973, it is believed that these trends roughly coincided in magnitude, providing approximate stability in the number of expatriates employed.

- 3 Since, however, such people remain non-nationals, they do have the option of returning to their home countries. Emigration, for them, is thus much more likely than for most members of the citizen labour force. From a supply-side point of view, therefore, it would be unwise to count automatically upon their continued presence, particularly under the recent circumstances of sharply declining incomes from wage and salaried employment.

- 4 The survey covered approximately 70 per cent of total formal employment in 1983. Focused, as it was, on the line-of-rail centres, a substantially higher proportion (perhaps 80 per cent) of non-Zambian employees was captured by the survey.

- 5 Daniel (1979sChapter 7) provides interesting evidence and argument to suggest that the period of mining wage leadership ended at a much earlier date - around 1960.

- 6 Calculated from Heesook et al. 1986: Appendix Table 6.
- H. Hotelling. The Economics of Exhaustible Resources. _Journal of Political Economy_ , 39(2):137–175, 1931. ISSN 0022-3808. URL `https://www.jstor.org/stable/1822328` .

- Intergovernmental Panel on Climate Change. _Climate Change 2021: The Physical Science Basis_ . Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 2021.

- Intergovernmental Panel on Climate Change. _Climate Change 2022: Mitigation of Climate Change_ . Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 2022.

- S. Jenkins, B. Sanderson, G. Peters, T. L. Fr ̈olicher, P. Friedlingstein, and M. Allen. The Multi-Decadal Response to Net Zero CO2 Emissions and Implications for Emissions Policy. _Geophysical Research Letters_ , 49(23):e2022GL101047, Dec. 2022. ISSN 0094-8276, 1944-8007. doi: 10.1029/2022GL101047. URL `https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL101047` .

- D. L. Kelly and C. D. Kolstad. Bayesian learning, growth, and pollution. _Journal of Economic Dynamics and Control_ , 23(4):491–518, Feb. 1999. ISSN 01651889. doi: 10.1016/S0165-1889(98) 00034-7. URL `https://linkinghub.elsevier.com/retrieve/pii/S0165188998000347` .

- M. J. Kotchen, J. A. Rising, and G. Wagner. The costs of “costless” climate mitigation. _Science_ , 382(6674):1001–1003, Dec. 2023. ISSN 0036-8075, 1095-9203. doi: 10.1126/science.adj2453. URL `https://www.science.org/doi/10.1126/science.adj2453` .

- N. J. Leach, S. Jenkins, Z. Nicholls, C. J. Smith, J. Lynch, M. Cain, T. Walsh, B. Wu, J. Tsutsui, and M. R. Allen. FaIR v2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration. _Geoscientific Model Development_ , 14(5):3007–3036, May 2021. ISSN 1991-9603. doi: 10.5194/gmd-14-3007-2021. URL `https://gmd.copernicus.org/articles/14/3007/2021/` .

- D. Lemoine. The Climate Risk Premium: How Uncertainty Affects the Social Cost of Carbon. _Journal of the Association of Environmental and Resource Economists_ , 8(1):27–57, Jan. 2021. ISSN 23335955, 2333-5963. doi: 10.1086/710667. URL `https://www.journals.uchicago.edu/doi/10.1086/ 710667` .

- D. Lemoine and I. Rudik. Managing Climate Change Under Uncertainty: Recursive Integrated Assessment at an Inflection Point. _Annual Review of Resource Economics_ , 9(1):117–142, Oct. 2017. ISSN 1941-1340, 1941-1359. doi: 10.1146/annurev-resource-100516-053516. URL `http: //www.annualreviews.org/doi/10.1146/annurev-resource-100516-053516` .

- D. Lemoine and C. P. Traeger. Economics of tipping the climate dominoes. _Nature Climate Change_ , 6(5):514–519, May 2016. ISSN 1758-678X, 1758-6798. doi: 10.1038/nclimate2902. URL `https: //www.nature.com/articles/nclimate2902` .

- T. M. Lenton, H. Held, E. Kriegler, J. W. Hall, W. Lucht, S. Rahmstorf, and H. J. Schellnhuber. Tipping elements in the Earth’s climate system. _Proceedings of the National Academy of Sciences_ , 105(6):1786–1793, Feb. 2008. ISSN 0027-8424, 1091-6490. doi: 10.1073/pnas.0705414105. URL `https://pnas.org/doi/full/10.1073/pnas.0705414105` .

22
Generally, this study confirms that fertilizer use which is clearly evident in maize production in Nigeria can be profitable<sup>26</sup> . However, at current input and output prices, this remains a reality for only a subset of maize farmers. Our study finds farmer observed practices to be closer to that expected of risk averse farmers and demonstrates the importance of accounting for risk preferences in modern input profitability considerations. Expanding the number of maize farmers that use fertilizer (and for which it is economically profitable at acquisition price) is still necessary in Nigeria. Currently only about 50% of maize plots use fertilizer. However, we find that many maize farmers in Nigeria are already applying nitrogen beyond levels considered economically optimal. While this is partly driven by low optimal rates given the high transportation costs, this indicates the need for further studies on fertilizer profitability in Sub-Saharan Africa. This study only focusses on maize but indicates issues that are likely to affect fertilizer use for other crops. See Liverpool-Tasie (2014) and Liverpool-Tasie et al. (2015) for the cases of rice and sorghum in Nigeria. More effort is needed to understand the rationale for the current nitrogen application rates across smallholder farmers and to increase the profitability of fertilizer use by addressing transportation costs and other factors (such as timeliness of availability and management practice) currently mitigating the yield and profitability effects of fertilizer use.

# **References**

<mark>‐ ‐ Abrar, S., Morrissey, O., & Rayner, T. (2004). Crop Level Supply Response by Agro Climatic Region in</mark>

> 26 A full scale profitability would be necessary to make this claim as fertilizer use has other dimensions such as increased labor demand for application and consequent weeding and this has not been taken into account yet.

31
**A12 Romania**

**Table A12: Regional disparity trends in Romania**

|Year|Max/Min<br>(MMR)|Simple<br>coefficient<br>of variation<br>(CVu)|Weighted<br>coefficient<br>of variation<br>(CVw)|Relative<br>mean<br>Deviation<br>(E.Rw)<br>..|Unweighte<br> <br>gini index<br>L..|d Weighted<br>gini index<br>(Gw)|<br>Theil<br>index<br>**(T)**|
|---|---|---|---|---|---|---|---|
|1993|1.693|0.171|0.156|0.111|0.095|0.081|0.010|
|1996|1.783|0.189|0.170.132||0.106|0.090|0.012|

# **Figure A12: Regional disparity trends** in Romania

<!-- Start of picture text --> 0.200 .<br>0.180 . L., <..'^,._ -. <- CtMS<br>0.180<br>0.160 < X , + . ..........a . ... s<br>0.140<br>0.120<br>.0 E {,'$'< '' i' A'.' *w tt;.',>,:Le '~ >W v<br>-A 'I .X , tl _ ' '.:, '.,.'@, "<br>0 0080 0 __080______________1_______________________ -_-_<br>.. .,.<br>0.060 ;p>; i.N.frita%8hjWtiJ%erSt , X ; > ,<br>0.040<br>0.020 ..<br>0 000- i ','''.. . !<br>1993 1996<br>Year<br><!-- End of picture text --> <!-- Start of picture text --> Simple coefficient of variation (CVu)<br>-- ' W eighted c oefficient of variaton (CVw)<br>- Relative mean Deviation (Rw)<br>) Unweighted gini index (Gu)<br>.' , t. +Weighted gini index (Gw)<br>--<br>Theil index (T)<br><!-- End of picture text --> 47
**Table 3: School Construction and Child Cognitive and School Curriculum Tests: Difference-in-differences estimates.**

||1966-1970|Maternal Cohort|Differen|ce in Diff|erences|
|---|---|---|---|---|---|
||High INPRES|High-Low INPRES||||
||Mean|Gap||||
||||[1]|[2]|[3]|
|Language (school curriculum) [age-specifc z-score]|0.08|-0.63|0.154|0.148|0.137|
||||(0.077)|(0.082)|(0.078)|
||||[0.052]|[0.096]|[0.096]|
|spaceChild in bottom quartile of age-specifc language score dist. (%)|39.4|28.9|-10.700|-10.975|-10.921|
||||(3.061)|(3.055)|(3.110)|
||||[0.016]|[0.008]|[0.008]|
|Mathematics (school curriculum) [age-specifc z-score]|0.04|-0.60|0.098|0.097|0.090|
||||(0.119)|(0.112)|(0.119)|
||||[0.524]|[0.512]|[0.528]|
|spaceChild in bottom quartile of age-specifc math score dist. (%)|33.7|25.0|-4.587|-4.938|-4.961|
||||(5.900)|(5.959)|(6.017)|
||||[0.492]|[0.556]|[0.528]|
|Cognitive reasoning [age-specifc z-score]|-0.11|-0.48|0.069|0.056|0.055|
||||(0.081)|(0.073)|(0.078)|
||||[0.428]|[0.456]|[0.520]|
|spaceChild in bottom quartile of age-specifc cognitive reasoning score dist. (%)|35.8|16.1|1.872|2.210|2.169|
||||(3.404)|(3.267)|(3.353)|
||||[0.632]|[0.600]|[0.676]|
|_Controls (D-in-D’s)_||||||
|Caregiver district and year of birth FE’s|||YES|YES|YES|
|Treated cohort interaction with # school-aged children in 1973 (ln scale)|||NO|YES|YES|
|Child gender|||YES|YES|YES|
|Child-age FE’s|||YES|YES|NO|
|Child’s age(linearly,in months)|||NO|NO|YES|

Notes: Sample is 2,118 children. Standard-errors in parentheses are clustered at the district of maternal birth. Wild-bootstrap significance p-values in brackets.