rafmacalaba/datause-encoder-data huggingface dataset:
|P074398|2003|2010|11/24/2009|16 Closed|Tunisia|
|---|---|---|---|---|---|
|P074398|2003|2011|11/18/2010|17 Closed|Tunisia|
|P074408|2002|2002|6/10/2002|3 Closed|Turkey|
|P074408|2002|2003|6/26/2003|5 Closed|Turkey|
|P074408|2002|2004|6/9/2004|7 Closed|Turkey|
|P074408|2002|2005|3/23/2005|12 Closed|Turkey|
|P074408|2002|2006|11/17/2005|13 Closed|Turkey|
|P074408|2002|2006|5/3/2006|14 Closed|Turkey|
|P074408|2002|2007|12/6/2006|15 Closed|Turkey|
|P074408|2002|2007|3/29/2007|16 Closed|Turkey|
|P074408|2002|2008|1/24/2008|17 Closed|Turkey|
|P074408|2002|2008|3/31/2008|18 Closed|Turkey|
|P074410|2002|2002|6/26/2002|1 Closed|Latvia|
|P074410|2002|2003|5/30/2003|3 Closed|Latvia|
|P074410|2002|2004|5/30/2003|3 Closed|Latvia|
|P074410|2002|2020|5/4/2020|4 Closed|Latvia|
|P074413|2004|2004|4/30/2004|1 Closed|Yemen,Republic of|
|P074413|2004|2005|3/10/2005|3 Closed|Yemen,Republic of|
|P074413|2004|2006|9/23/2005|4 Closed|Yemen,Republic of|
|P074413|2004|2006|12/19/2005|5 Closed|Yemen,Republic of|
|P074413|2004|2006|5/26/2006|6 Closed|Yemen,Republic of|
|P074413|2004|2007|12/20/2006|7 Closed|Yemen,Republic of|
|P074413|2004|2007|6/25/2007|8 Closed|Yemen,Republic of|
|P074413|2004|2008|12/5/2007|9 Closed|Yemen,Republic of|
|P074413|2004|2008|4/9/2008|10 Closed|Yemen,Republic of|
|P074413|2004|2008|6/2/2008|11 Closed|Yemen,Republic of|
|P074413|2004|2009|12/30/2008|12 Closed|Yemen,Republic of|
|P074413|2004|2009|6/15/2009|13 Closed|Yemen,Republic of|
|P074413|2004|2010|12/30/2009|14 Closed|Yemen,Republic of|
|P074413|2004|2010|3/18/2010|15 Closed|Yemen,Republic of|
|P074413|2004|2011|11/28/2010<br>|16 Closed|Yemen,Republic of|
|P074413|2004|2011|6/29/2011|17 Closed|Yemen,Republic of|
|P074413|2004|2012|8/10/2011|18 Closed|Yemen,Republic of|
|P074413|2004|2012|6/19/2012|19 Closed|Yemen,Republic of|
|P074414|2005|2005|4/21/2005|2 Closed|Vietnam|
|P074414|2005|2006|11/14/2005|3 Closed|Vietnam|
|P074414|2005|2007|7/9/2006|4 Closed|Vietnam|
|P074414|2005|2007|2/24/2007|5 Closed|Vietnam|
|P074414|2005|2008|7/28/2007|6 Closed|Vietnam|
|P074414|2005|2008|5/8/2008|7 Closed|Vietnam|
|P074414|2005|2009|5/18/2009|8 Closed|Vietnam|
|P074414|2005|2010|1/15/2010|9 Closed|Vietnam|
|P074414|2005|2011|11/6/2010|10 Closed|Vietnam|
|P074414|2005|2012|11/13/2011|11 Closed|Vietnam|
|P074414|2005|2013|9/16/2012|12 Closed|Vietnam|
|P074414|2005|2013|5/27/2013|13 Closed|Vietnam|
|P074414|2005|2014|2/19/2014|14 Closed|Vietnam|
margins are not merely the result of cost cutting. Since privatization, the number of branches decreased only slightly, if.at all, for each bank.32 Although some labor shedding has occurred, in no case has the work force been reduced by more than 15%. In summary, the data indicate that remaining employees generate profit far more efficiently than before. This suggests that the banks' loan portfolios became far more commercially oriented after privatization. Credit allocation data presented in the next sub-section provides additional support for this hypothesis.

**Table 8: Ratios of Income to Costs Before and after Privatization**

||Fin<br>Inc/<br>Costs|Serv<br>Inc/<br>Costs|Total<br>Inc/<br>Costs|Assets<br>.|Liabil.|Net<br>Worth|Depo-<br>sits|Loans|#<br>Bra<br>nch|#<br>Em-<br>ploy.|Date|
|---|---|---|---|---|---|---|---|---|---|---|---|
||Mean|Mean|Mean|Pesos<br>000s|Pesos<br>IOOOsS|Pesos<br>OOOs|Pesos<br>IOOOs|Pesos<br>I000s||||
|**Chaco**||||||||||||
|Before|-.379|.173|-.206|42883|34483|8400|10950|140|28|615|11/94|
|After|.683|.683|1.366|220335|207088|13247|130995|63012|28|547|10/96|
|**EntreRios**||||||||||||
|Before|-.161|.461|.300|395548|384548|11000|211900|226121|_55_|1542|1/95|
|After|.726|.521|1.247|667609|614133|53476|503221|372225|68|1340|11/96|
|Formosa||||||||||||
|Before|-1.589|.270|-1.319|26569|11569|15000|11569|5489|10|230|12/95|
|After|.318|.733|1.051|129578|113064|16514|97379|77946|10|221|11/96|
|**Misiones**||||||||||||
|Before|-.530|.333|-.197|70498|61498|9000|48131|47325|30|433|2/96|
|After|.475|.890|1.364|157543|142820|14723|105159|77999|29|422|11/96|
|Rio Negro||||||||||||
|Before|.333|.472|.805|49162|47362|1800|42212|41767|21|425|3/96|
|After|.610|.524|1.134|134984|122142|12842|87640|85988|29|416|11/96|
|Salta||||||||||||
|Before|3.090|.289|3.379|58941|52711|6230|40892|18000|16|260|3/96|
|After|2.381|.842|3.223|250860|240924|9936|201988|173074|15|301|11/96|
|Data Sources:|B.C.R.A.|and Fondo|Fiduciario|||||||||

Notes: The data on income and costs cover only 1993-96. Since Corrientes privatized in 1992, no pre-privatization data was available. For La Rioja, which privatized in 1994, pre-privatization data were not available because the bank had suspended operations in 1993. This leaves only the six cases listed above.

32 In some instances, owners of privatized banks are required to maintain a certain number of branches under the terms of their purchase agreements.

19
who continue to work on low-income countries are not rewarded in the publication (and hence tenure) process, there may be efficiency losses in terms of the networks that they have access to.

At this stage, our findings consist of tabulations and correlations. Like all work on discrimination, identifying differential treatment in any form is difficult in the absence of experimental studies.<sup>4</sup> Furthermore, with sparse information on the availability and quality of datasets from different countries, it is ultimately difficult to rule out the influence of data on the quantity and quality of publications across countries. The findings presented in the paper thus aim only to book-end a debate on why there is more research on some countries than others and on the publication process in the economics discipline, with a focus on empirical studies on and outside the US.

The remainder of the paper is as follows. Section 2 is the description of the data. Section 3 documents and discusses the two main findings of the paper. Section 4 concludes.

# **2. Data Description**

The main data source is constructed using information on journal articles published in selected 202 economics journals during the period 1985-2004 that were associated with a geographical identifier (thus excluding all theoretical contributions and cross-country empirical work). We used journal rankings proposed by Kalaitzidakis and others (2003) and Kordrzycki and Yu (2006) to finalize the list of journals for inclusion in the database. Ultimately, we selected the 202 economics journals that appeared at least in one of their proposed rankings. Table A1 provides the list of these journals and their rankings according to various citation indices. The large number of journals was chosen partly to ensure that country-specific publications in the dataset reflected the volume of research on the country rather than journal selectivity; of note is that the citation index for the bottom ranked 11 journals is 0, and close to 75 journals have a citation rank less than 1 (that is, the average article in the journal is cited less than once in subsequent research).<sup>5</sup>

> 4 Previous work examines whether top economics journals are biased in their publication rates towards authors in the editor’s networks as well as how the introduction of double-blind review changed the publishing process (Laband and Piette, 1994, Blank 1991). 5 Kalaitzidakis and others (2003) construct for each journal a citation rank based on citations in 1998 of articles published only in 1994-1998, excluding self-citations and adjusted for impact (influence) and size. Kordrzycki and Yu (2006) provide citations and reference-intensity-adjusted rankings that evaluate a specified set of journals according to influence of journals and influence of journal articles. These rankings take into account citations in economics academic

5
|**Table 5: Households’ knowledge of the la**|**nd law**<br>|||||||<sup>**b**</sup>|
|---|---|---|---|---|---|---|---|---|
||**Total**<br>**Sample**|**Tigray**|**Amhara**|**Oromia**|**SNNPR**|**LAC M**<br>**Yes**|**ember**<br>**No**|**LAC**|
|**Tenure security**|||||||||
|Households’ land use rights w. migration|87.39|52.89|94.80|95.95|77.66|87.82|87.34|90.09|
|Inheritance to people other than children|39.61|7.44|19.35|56.37|43.22|39.08|39.67|46.91|
|Mortgaging use rights allowed|43.80|59.09|35.13|49.32|34.24|49.58|43.14|51.85|
|**Land transfers**:|||||||||
|Less than the maximum rental period<sup>a</sup><br>|89.50|88.43|88.71|90.15|89.56|91.60|89.26|87.99|
|Know maximum rental period<sup>a</sup>|1.56|0.00|1.97|1.16|2.71|3.36|1.35|*<br>9.12|
|Less than needed years to register rental|35.21|26.86|47.67|34.17|27.14|26.05|36.25|*<br>37.42|
|Registration of rental contracts|40.95|48.35|24.19|52.99|30.69|47.48|40.20|*<br>44.44|
|**Gender aspects**|||||||||
|Division of land in case of divorce|86.61|99.59|99.46|80.89|77.45|85.29|86.76|80.18|
|Number of observations|2315|242|558|1036|479|238|2077|111|

_Source:_ Own computation from 2006 EEA/WB Land certification survey. Stars indicate the significance of differences between LAC members and non-members: * significant at 5%; ** significant at 1%. a For modern technology only. b The average score of three LAC members from the community survey.

25
sugarcane is considered economically and environmentally superior to using corn. But by reducing the volume of trade, some barriers actually enhance welfare. One instance where this can be true is when biofuel production has environmental externalities that are not taken into account. Biofuels will also affect trade by reducing food surpluses in developed countries, which will reduce both food exports and food aid. This will allow farmers in poor importing countries to receive higher prices, which can be an opportunity to increase productivity especially in those countries. The literature on linkages between biofuels and international trade is at a nascent stage and needs to be expanded further.

Given the spectrum of agricultural and trade effects, the only conclusive statement one could make about the environmental impact of biofuels is that it is hard to generalize. Biofuels will have both environmental benefits and costs, and these are difficult to compare. They may reduce carbon emissions, but there will be negative impacts from increased agricultural activity, which will be important on a local if not global scale. The current literature has focused too much on carbon offsets to the exclusion of other environmental effects. Depending on whether forestland is converted to agricultural land, whether a perennial or annual crop is grown, whether the crops are grown as a monoculture or polyculture, whether they are irrigated or rain fed, whether they are grown organically, etc., the impacts will vary too. Existing tools like LCA provide aggregate information for a limited set of environmental indicators, but future research will need to estimate both a broader set of indicators and also differentiate them with location and time. A related area of future work should be in monitoring and evaluation of production practices. Ensuring adherence to sustainable practices will require development of labeling and certification procedures. Economists and policymakers will have to consider the costs of implementing such procedures and its impact on the competitiveness of biofuels.

In addition to the above themes, there are several others we think should be part of the future research agenda. For instance, formal economic models predict the impact on the poor solely based on market price of food or other commodities. While this may be sufficient in the context of fully developed market economies, the importance of informal 76
# **Table C3: Determinants of Life Satisfaction in developing MENA: Alternative Variable Specifications (OLS)**

|VARIABLES|(1)<br>Alternative<br>standards of<br>living|(2)<br>Alternative<br>job<br>opportunities|(3)<br>Alternative<br>civil freedom|(4)<br>Alternative<br>widespread<br>corruption|
|---|---|---|---|---|
|Food and Shelter Index|-0.976***<br>(0.059)||||
|Would you say that it is now a good<br>time or a bad time to find a job: Bad<br>time||-0.141***<br>(0.033)|||
|Do you have confidence in each of the|||-0.029||
|following? How about the quality and<br>integrity of the media: No|||(0.042)||
|Level of corruption is higher||||-0.081***|
|People cannot get ahead by working<br>hard: Yes|-0.305***<br>(0.042)|-0.195***<br>(0.040)|-0.225***<br>(0.057)|-0.200***<br>(0.039)|
|Dissatisfied with the educational<br>system or the schools: Yes|-0.252***<br>(0.034)|-0.150***<br>(0.031)|-0.166***<br>(0.043)|-0.169***<br>(0.030)|
|Individual characteristics|YES|YES|YES|YES|
|Country fixed effects|YES<sup>A</sup>|YES<sup>B</sup>|YES|YES|
|Month and year of interview|YES|YES|YES|YES|
|Constant|6.470***|5.865***|5.902***|5.676***|
||(0.200)|(0.180)|(0.267)|(0.177)|
|**Observations**|21,376|23,592|10,926|24,012|
|R-squared|0.162|0.207|0.220|0.210|

_Note:_ Robust standard errors are in parentheses. ***p < .01; **p < .05; *p < .10.

A Morocco and Syria are missing.

B Morocco is missing.

38
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**_Energy demand models for policy_** **_<u>formulation</u>_**

. . Xn* = dn(p1, <u>p2, p3, ...pn, I)</u> Source: Bohi (1981).

An individual demand curve shows the relationship between the price of a good and the quantity of that good purchased, assuming that all other determinants of demand are held constant. The market demand function for a particular good is the sum of each individual’s demand for that good. The market demand curve for the good is constructed from the demand function by varying the price of the good while holding all other determinants constant.

# **3.1.2 Industrial and commercial energy demand**

In the case of industry and commercial sectors, energy is used as an input to produce an output (or outputs). The theory of the producers is used to determine energy demand in both sectors. Like households, producers face certain constraints:

- a) The production process has its own technical limitations that specify the maximum output levels for a given combination of inputs.

- b) The capacity of the plant at any given time is fixed and cannot be exceeded.

- c) There may be constraints on the availability of certain inputs.

Production of any good is expanded until an additional increment of the good produced in the most efficient manner makes no further contribution to net revenue. Similarly, any factor of production will be increased until, other inputs remaining unchanged, an additional unit of the factor yields no additional net revenue. In order to minimize the cost of any given level of input, the firm should produce at that point for which the rate of technical substitution is equal to the ratio of the inputs’ rental prices. The solution of the conditions leads to factor demand functions. Box 2 provides the mathematical formulation of the above.

19
3.72 for advanced European countries, 3.58 for the former Eastern European countries, and 3.80 for the US. These differentials in average wellbeing across sectors may partly reflect the long-established finding that life satisfaction increases more generally with income (see Clark and Senik (2010b) for a recent review). However, other factors are likely to be important as well, as is suggested by the greater average satisfaction of workers in Bangladesh (3.69, $US 700) which tend to be poorer.<sup>15</sup> More striking are the relative rankings within Ghana. Civil sector employees and selfemployed individuals who employ others report the highest levels of job satisfaction. The difference between their job satisfaction levels is not statistically significant, even though civil sector workers earn significantly more than the self-employed who employ others. Conversely, while the average earnings of wage employees in large firms are not significantly lower than those for self-employed workers who hire other workers, their self-reported job satisfaction is significantly lower. The workers with the lowest levels of earnings and job satisfaction are wage workers in small enterprises. The standard deviations of the job satisfaction measure are large pointing towards substantial heterogeneity in satisfaction within sectors. Life and financial satisfaction exhibit similar patterns, though it is worthwhile noting that the self-employed who employ other have marginally higher levels of average life and financial satisfaction than public sector employees, and that the self-employed without employees are on average more satisfied with their financial situation than the formal salaried.

Clearly, it is desirable to both more rigorously model the discrete nature of the subjective responses and to condition on individual characterstics. In the next section, we begin with the commmon fixed parameter ordered probit to provide baseline results. We then employ the random parameter ordered probit estimations to examine the distribution of preferences around the mean tendencies.

> 15A rudimentary rescaling of findings from Blanchflower (2000) gives an average value of 3.88 for the OECD.

15
Table 6: IV regression: The effect of migration on land tenure arrangements, using the residual approach

||(1)<br>fxed rent|(2)<br>fxed (money)|(3)<br>fxed (crop)|(4)<br>sharecropping|(5)<br>relatives|(6)<br>contract length|(7)<br>written contract|
|---|---|---|---|---|---|---|---|
|migration|2.682***|2.182***|0.500|-1.882**|-0.916|0.150|0.462|
||(0.855)|(0.663)|(0.517)|(0.886)|(0.587)|(0.745)|(0.427)|
|bank branches (number)|-0.0265|-0.00269|-0.0239*|0.00156|0.0325*|0.000205|0.0232|
||(0.0245)|(0.0207)|(0.0131)|(0.0257)|(0.0174)|(0.0200)|(0.0153)|
|road length (km)|-0.000742|-0.000636|-0.000106|0.000631|0.000103|0.00166***|-0.000557|
||(0.000641)|(0.000558)|(0.000322)|(0.000560)|(0.000351)|(0.000476)|(0.000348)|
|2012 year|-5.722*|-3.255|-2.466|-3.920|7.915***|22.51***|3.766**|
||(3.428)|(2.998)|(1.972)|(3.048)|(1.977)|(2.685)|(1.882)|
|observations|878|878|878|878|878|878|878|
|mean dep. var.|45.34|27.83|17.51|34.13|4.92|36.90|11.25|

Note: This table uses the residual shift-share instrumental variable regression to present the relation between the percentage of rented-in acreage under various terms and the number of high-skilled male out-migrants between the ages of 20-64 years (as a percentage of the total male out-migrants between the ages of 20-64 years). The population controls include total population, sex ratio, population density and share of high-skilled males. Remaining controls include the percentage of adverse rain events and the percentage of adverse temperature events. The dependent variable is as a percentage of acreage of rented in land. Robust standard errors. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.
ETHIOPIA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Prices of ICT services in Ethiopia are also very low—except for international calls—and much lower than in the rest of Africa. For example, a standardized monthly basket of mobile telephone services costs $3.37 in Ethiopia compared with the African benchmark of $11.12. Such low tariffs for domestic mobile (and fixed) services seem to be supported by cross subsidies from international call charges, which are substantially higher than the African benchmark. This is because ICT tariffs in Ethiopia have not yet been rebalanced to bring them closer into line with cost structures, a move that most African countries have undertaken to prepare the market for competition. Surprisingly, the low cost of services does not seem to have promoted wider access to these services in Ethiopia.

Ethiopia’s central challenge is to introduce competition to the ICT sector. The Ethiopian market could potentially experience the same explosive growth of GSM coverage as has taken place across Africa. To make the transition, the country needs to modernize the sector’s institutional and regulatory framework, which is among the least developed in Africa. Ethiopia scores only 28 percent on an AICD index of institutional reform that captures the extent to which countries have modernized in terms of sector reform, regulatory framework and governance of state-owned ICT incumbents, compared with around 50 percent for the median African country (figure 10). The key step would be to license a second mobile operator in the market, and eventually additional ones. In addition to accelerating the expansion of GSM coverage, such a move has the potential to raise significant fiscal resources for the government—based on the experience if the 2000s in Africa, the license could potentially raise at least $0.5 billion.

**Table 6. Benchmarking ICT infrastructure**

||Unit|**Ethiopia**|Low-income countries|
|---|---|---|---|
|GSM coverage|% population|**9.9**|48.2|
|International bandwidth|Mbps/capita|**0.3**|5.8|
|Internet|subscribers/100 people|**0.0**|0.1|
|Landline|subscribers/100 people|**1.0**|0.8|
|Mobile phone|subscribers/100 people|**1.6**|15.1|
|**Prices**($)|**Ethiopia**|Without submarine cable|Other developing regions|
|Price of monthly mobile basket|**3.37**|11.12|9.9|
|Price of monthly fixed line basket|**2.00**|13.58|—|
|Price of 20-hour Internet package|**14.85**|67.95|11.0|
|Price of a 3-minute call to United States|**3.33**|2.59|2.0|
|Price of inter-Africa telephone calls, mean|**1.27**|0.72|n.a.|

_Source_ : Minges and others 2008. — = Data not available. n.a. = Not applicable.

16