rafmacalaba/datause-encoder-data huggingface dataset:
4International Energy Agency.

- 5International Monetary Fund, International Financial Statistics and Balance of Payments databases, World Bank, Global Development Finance, and World Bank and OECD GDP estimates. 6World Trade Organization, and World Bank GDP estimates.

7United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.

8International Labour Organization.

12United Nations Conference on Trade and Development, Handbook of Statistics, and International Monetary, International Financial Statistics.

13United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.

14Note: Break in series between 1997 and 1998 due to due to change from International Standard Classification of Education (ISCED76) to ISCED97. Recent data are provisional.

Source: World Bank‘s World Development Indicators (2009).

Table 3 Sources of productivity growth by sector for 1996-2006.

|**Sector Mean**|**Technical**<br>**Efficiency**<br>**Change**<br>**(TEC)**|**Technical**<br>**Change**<br>**(TC)**|**Scale**<br>**Efficiency**<br>**Change**<br>**(SEC)**|**Total**<br>**productivity**<br>**Change**<br><br><br>0<br>_G_|
|---|---|---|---|---|
|Argentina|-0.018|-0.598|8.943|8.328|
|Bolivia|0.003|1.131|-31.481|-30.347|
|Brazil|-0.001|0.072|-20.542|-20.471|
|Chile|0.004|-0.978|7.605|6.631|
|Costa Rica|-0.049|2.305|2.986|5.242|
|Ecuador|-0.044|1.126|-0.980|0.103|
|El Salvador|-0.039|1.447|5.427|6.834|
|Guatemala|-0.049|0.687|-5.285|-4.647|
|Honduras|-0.066|2.202|10.610|12.746|
|Mexico|-0.006|-0.873|24.829|23.950|
|Nicaragua|-0.022|0.873|-6.197|-5.347|
|Panama|-0.050|2.296|2.930|5.176|
|Paraguay|0.036|0.669|-48.384|-47.679|
|Peru|-0.053|4.175|-7.457|-3.336|
|Uruguay|0.006|2.843|-16.183|-13.334|
|Venezuela,RB|-0.053|-3.023|53.662|50.586|
|Total|-0.025|0.897|-1.220|-0.348|

Source: Author‘s calculations.

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# III. INTEGRATION AND COINTEGRATION TEST RESULTS

# (a) Integration Test

8. Tables 1 and 2 report the Sargan-Bhagrava (CRDW), Dickey-Fuller (DF) and Augmented Dickey-Fuller (ADF) test statistics for the 13 series listed. The first five series are price indices for various primary commodity groups and are expressed in deflated terms. All other series are also expressed in real terms. The ADF test was also carried out after fitting various lags to the data, where the number of lags were sufficient to ensure that the residual _ is white noise (these results are in column 5 of Tables 1 and 2). Results **of** the Lagrange Multiplier test for third order residual autocorrelation, LM(3)--distributed as X2 in large samples, under the null hypothesis that there is no autocorrelation--are presented in the sixth column of the tables (the critical value at 95% level of significance for X is 7.81). 3 9. The integration tests of the untransformed data (Table 1) showed that all the series, regardless of the sample period, are non-stationary at the 99% level of significance. Therefore, we tested whether the rate of change of the variables was stationary. From the test results on the first-differenced series in Table 2 it appears that all the series, apart from the first difference of the consumer price index for the major 7 OECD countries, CPIG7, are stationary at the 99% level. The CPIG7 series must be differenced twice to become stable at the same level of significance. Thus, CPIG7 is integrated of order two, I(2), while all the other series have a unit root. Therefore, a
predictive power beyond that offered by correlates of expectations, such as socioeconomic characteristics and current levels of the outcome of interest. In this section we summarize the results of several studies and provide additional evidence which together do suggest that expectations are useful in predicting behavior and future outcomes.

# _5.1 Do subjective expectations predict future outcomes? Are they accurate?_

The first question of interest is whether the expectations about future events elicited from people in developing countries are informative about the likelihood of these future events occurring, and if so, how accurate these expectations are. The available evidence seems to suggest that the expectations are indeed informative of future events, with people more likely to experience an event typically giving a higher elicited expectation of such an event occurring. The accuracy of these expectations has been found to be high for reasonably common, regularly occurring events, but less accurate for rare or unexperienced events.

An early example showing reasonably accurate expectations of common events is found in work by Ravallion (1987), who asked rice traders in Bangladesh whether they thought the price would go up, go down, or stay the same, and the amount of change. Expectations were found to track prices fairly well on average, although there was a tendency to overestimate price changes. More recently, reasonably accurate expectations have been found in several agricultural contexts. For example, Luseno et al. (2003) find pastoralists in Ethiopia and Kenya have reasonably accurate perceptions of rainfall and Lybbert et al. (2005) show that these same pastoralists update their expectations when they receive external climate forecasts. In a more complicated elicitation, Santos and Barrett (2006) elicit both expectations for rainfall next year, and of herd size next year, and show that Ethiopian herders’ expectations of herd size vary with rainfall in a way which matches well the nonstationary herd dynamics that herd history data would suggest.

However, recent studies have also shown that in a context of incomplete information, expectations can be quite inaccurate, even if they predict future outcomes. Jensen (2006) finds school children in rural Dominican Republic significantly understate the returns to education, which he attributes in part to adults with education migrating to cities, leaving children in rural areas with little information about the earnings and jobs that education brings. A related finding is seen in McKenzie et al. (2007), who show that Tongans dramatically underestimate the

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by many factors (altruism, political ideology and values), while demand for redistribution to the middle class appears to be driven by self-interest and knowledge of the tax system.

Although the middle class is not at the core of their analysis, a recent study by Cruces, Pérez Truglia and Tetaz (2011) provides relevant evidence on how individuals form perceptions with strong biases to the evaluation of their own relative position in the distribution. Using data for the Greater Buenos Aires, they assess the relevance of such biases by examining their impact on attitudes towards redistributive policies. An important characteristic of the survey lies in its experimental design, as the interviewer informs a randomly selected group of respondents whether their subjective income position coincides with the objective figures. They find that respondents who were relatively poorer than they had thought became more supportive of redistribution to the poor when informed of their true income rank, while for those with negative biases (i.e. who were relatively wealthier than they had thought), there are no significant results.

# 3. Data and methodology

Our analysis draws on the 2007 _Ecosocial_ values surveys. These values surveys were implemented by CIEPLAN, a Latin American Think Tank, in seven Latin American countries – Argentina, Brazil, Chile, Colombia, Guatemala, Mexico and Peru. The surveys are representative of the adult population (18 years or more) living in larger urban centers in each country. The sampling design is probabilistic and multistage, and the questionnaire was applied through face-to-face interviews in the respondents’ household. We choose to use the _Ecosocial_ surveys because of their rigorous sampling methodology, the information they collect on a variety of values, and because they collect information about households’ assets, which will allow us to construct a measure of households’ permanent income (see below). We exclude from the analysis Argentina because we were not able to match assets with other surveys and build an income measure. The analysis is therefore based on a pooled dataset combining six countries that was created from the national datasets, with a total sample size of 12,297 observations.

The outcomes of interest, our dependent variables, are the values and attitudes regarding political, economic, and social issues. Because of the large number of questions asked in the surveys, and likely similarity of answers within themes, we group questions using principal component analysis (PCA), and create thematic “values indexes.” Principal component analysis reduces the dimensionality of a data set with a large number of interrelated variables, while retaining as much 6
As for DR export goods, the sectors (HS 2-digits) with the largest exports to the CAFTA members in 2008 were plastics (22%), cotton (20%) and tobacco (19%). These sectors combined, accounted for 61% of total exports to the CAFTA area. Particularly noteworthy is the textile sector, which went from US$ 1.1 in 2005 to US$ 18.3 million in 2008. This increase was mainly due to a surge in the exports of cotton (i.e. US$ 11.5 million). In the case of the U.S., the main export sectors were apparel (20%), medical and chirurgical instruments (16%), machinery and electrical appliances (14%) and jewelry (14%) (see Appendix 3). These sectors have increased their share in total exports since 2005, except for the clothing sector.

Figures 3a and 3b: Exports to CAFTA members <!-- Start of picture text --> Exports to the CAFTA area Exports to CAFTA members (selected years)<br>El Salvador Guatemala Honduras Nicaragua<br>2002 2003 2004 2005 2006 2007 2008 2009 2003 2005 2007 2008<br>year<br>60 40<br>50<br>30<br>40<br>30 20<br>in US $ millions<br>20 Exports in US$ million<br>10<br>10<br>0<br>0<br><!-- End of picture text --> To summarize, following the DR-CAFTA agreement, exports to the U.S. stagnated in absolute terms while exports to the other CAFTA members exhibited strong growth, but their share represents only 1%. This highlights the potential for further trade expansion among Central American countries. However, in both cases, exports drop in 2009, probably as a consequence of the global economic crisis at that time.

# **4. Firm-level extensive margin patterns**

Having analyzed the aggregate exports patterns, we now examine the exporters’ dynamics that lied behind the aggregate exports movements. In particular, we look at firms’ export extensive margin to the U.S. and to CAFTA area to assess whether there are significant changes in the exporters’ behaviour subsequent to the agreement. The extensive margin refers to all new trade relationships<sup>12</sup> and can be decomposed into four components<sup>13</sup> :

- Exports by existing firms of a new product to a new market;

- Exports by existing firms of  a new product to an existing market;

- Exports by existing firms of an existing product to a new market; and

- Exports by new firms.

> 12 A trade relationship is defined as the combination of a firm, a product and a destination.  A new trade relationship can therefore be generated by the participation of new firms, the introduction of new products or/and the introduction of new markets.

> 13 Our unique dataset contains information at the firm, product and destination level which allows for such decomposition.

8
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45. Such a paradigm may be particularly appropriate in countries with heavy rail freight densities and virtually no competing transportation modes. In addition, the competitive access model can be applied to _groups_ of countries, the national railways of each would function as the "regional" entities assumed in the paradigm.

46. Over a broad range of applications, this paradigm evokes two critical issues: trackage use charges and regulation.

47. Trackage use charges. Both the structure and level of the trackage fees will be important in determining how well this approach would work. If the fee _levels_ are too high (reflecting inefficiency in the cost of providing capacity), then traffic will be depressed. The identical "tolls" for all users would provide some incentive for the owning railway to control its costs. Similarly, the development and publication of comparative maintenance cost statistics among the regional railways would identify poor performers and lead to pressure from the marketing departments. No matter what else happens, the principle must be established that the fixed facility cost centers must recover from users all their costs (so that fee levels are not too low). As explained in detail under "technical considerations" in Chapter 3, the fee _structure_ is vital because it can determine the way in which the operators perceive their incentives to design services, load wagons, organize trains, and so forth. For example, a fee structure based on axles (weighted by tonnes per axle), trains, and track usage time (weighted by peak hours versus off-peak hours) would provide an incentive to run heavy wagons (subject to the axle load weights), long trains, adequate power (in order to reduce running time and the costs of delay due to locomotive failure), and at the right times (due to peak charges). To be fair, the fixed facility cost center would probably have to provide a rebate based on the number of minutes of delay caused by problems (dispatching errors, track maintenance, signal failure, and the like) which were not the fault of the train operator. By contrast, a fee structure solely based on wagon-kilometers (as is common in the U.S.) would reduce the incentive to run long and full trains.

48. Regulation. Depending on the economic conditions and transportation environment of the country or countries adopting this paradigm -- in particular, if no inter- or intramodal transportation competition to the state railway now exists -- rate and service regulation may prove necessary. This regulation might base itself on such principles as the following:

- Non-discrimination between essentially similar shippers under similar circumstances (useful in principle, although almost unenforceable in practice);

- No single rate can exceed its variable (avoidable) cost by an excessive amount without good reason. In the U.S., this amount is 100 percent (i.e., the rate cannot be more than twice the variable cost), but almost any other target can be established.

- The overall rate of return earned by the regional railway as a whole would have to be at or near the opportunity cost of capital.
imply that every application will automatically be approved, it can help both parties to be more clear about the rules of the game from the beginning and, in addition, significantly reduce the search cost to be incurred by individual beneficiaries.

# 3.2.2 **Formulation of productive projects**

To help beneficiaries assess the requirements, opportunities, and risks they will face as independent farmers more realistically, elaboration of model farm projects has proved to be critical. While these models are necessarily abstract and therefore not directly applicable to the circumstances of specific beneficiaries or farms, they enable beneficiaries and technical assistance providers to be more specific about key factors such as marketing channels, input supplies, working capital requirements, etc. that need to be made more concrete during the subsequent process.

Under the approach followed by INCORA, where agricultural productivity received little if any consideration, beneficiaries generally elaborated their "productive projects" _after_ getting access to the land, with little systematic guidance and no discretion in the use of the technical assistance funds which were administered by INCORA (often with "beneficiaries" receiving no benefits at all). Without a clear understanding of the economic potential of the farms to be established, expected returns, and alternative options (within or outside the land reform program), beneficiaries' ability to engage in substantive bargaining was greatly diminished. It was only natural that INCORA took the lead in "negotiating" with the landlord; 27 a type of negotiation which ordinarily amounted to a mere formality and generally resulted in acceptance of the price set by an "independent" valuer who was contracted by the landlord and paid in proportion to the assessed farm value.

The pilot experience has indicated that, unless beneficiaries have a clear idea of productive opportunities consistent with their abilities _before_ they formulate productive projects that form the basis for "shopping" for land, it is very difficult to break this deadlock. To this end, agricultural professionals that are contracted through beneficiary representatives help establish crop budgets for a range of options actually practiced in the _municipio_ and conduct training courses and meetings to disseminate them. Aggregation of these into farm plans involving more intensive land use and sustainable income to beneficiaries provides the basis for the formulation of "productive projects" by individual beneficiaries. Only after

> effective form of satisfying demands for land. Due to the Imiited extent of the pilot, no such cases have, as of yet, been encountered. R7 This perception is illustrated by the fact that official records for the land transferred in 1996 indicate that in all cases where no credit from Caja Agraria was needed (because the seller advanced the 30% complementary credit to the buyer), a farm plan or productive project was "not required".

16
- Goldfarb, A. and Tucker, C. (2011 _a_ ), ‘Online display advertising: Targeting and obtrusiveness’, _Marketing Science_ **30** (3), 389–404.

- Goldfarb, A. and Tucker, C. E. (2011 _b_ ), ‘Privacy regulation and online advertising’, _Management science_ **57** (1), 57–71.

- Gordon, B. R., Jerath, K., Katona, Z., Narayanan, S., Shin, J. and Wilbur, K. C. (2021), ‘Inefficiencies in digital advertising markets’, _Journal of Marketing_ **85** (1), 7–25.

- Hayes, R. J. and Moulton, L. H. (2017), ‘Cluster randomised trials, second edition’, _Cluster Randomised Trials, Second Edition_ pp. 1–398.

- India IIPS (2022), _India national family health survey NFHS-5 2019-21._ , International Institute for Population Sciences - IIPS/India and ICF, Mumbai, India. **URL:** _https://www.dhsprogram.com/pubs/pdf/FR375/FR375.pdf_

- Johnson, G. A. (2023), ‘Inferno: A guide to field experiments in online display advertising’, _Journal of economics & management strategy_ **32** (3), 469–490.

- Johnson, G. A., Lewis, R. A. and Reiley, D. H. (2017), ‘When less is more: Data and power in advertising experiments’, _Marketing Science_ **36** (1), 43–53.

- Johnson, G. A., Shriver, S. K. and Du, S. (2020), ‘Consumer privacy choice in online advertising: Who opts out and at what cost to industry?’, _Marketing Science_ **39** (1), 33–51.

- Kotler, P. and Levy, S. J. (1969), ‘Broadening the concept of marketing’, _Journal of marketing_ **33** (1), 10–15.

- Kotler, P. and Zaltman, G. (1971), ‘Social marketing: an approach to planned social change’, _Journal of marketing_ **35** (3), 3–12.

- Lambrecht, A. and Tucker, C. (2019), ‘Algorithmic bias? an empirical study of apparent genderbased discrimination in the display of stem career ads’, _Management science_ **65** (7), 2966–2981.

- Lewis, R. A. and Reiley, D. H. (2014), ‘Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on yahoo!’, _Quantitative Marketing and Economics_ **12** , 235–266.

- Lindell, M. K. and Perry, R. W. (2012), ‘The protective action decision model: Theoretical modifications and additional evidence’, _Risk Analysis: An International Journal_ **32** (4), 616–632.

- Miaskiewicz, T. and Kozar, K. A. (2011), ‘Personas and user-centered design: How can personas benefit product design processes?’, _Design studies_ **32** (5), 417–430.

- Miller, G. and Mobarak, A. M. (2015), ‘Learning about new technologies through social networks: experimental evidence on nontraditional stoves in bangladesh’, _Marketing Science_ **34** (4), 480–499.

- Najafi, M., Ardalan, A., Akbarisari, A., Noorbala, A. A. and Elmi, H. (2017), ‘The theory of planned behavior and disaster preparedness’, _PLoS currents_ **9** .

- Narasimhan, L., Srinivasan, K. and Sudhir, K. (2015), ‘Marketing science in emerging markets’, _Marketing Science_ **34** (4), 473–479.

- Nielsen, L. (2013), _Personas-user focused design_ , Vol. 15, Springer.

- Orozco-Olvera, V. H. and Malhotra, N. (2023), _Media and Health Outcomes_ , Springer International

38
<!-- Start of picture text --> Slovenia DASHBOARD Formal enploynent:$37.34K<br>Total domestic SOEs: $93<br>Presence of SOEs Economic role in the market (domestic SOEs only)<br>aDsa a7 Domesticformal employmentSOEs share(%)in Domestic(%SOEs GDP)revenues<br>SOE density Presence of Siovenia SOEs - ~ —_<br>(SOEs per 100k inhabitants) in 42 countries ‘ = ia as<br>0 me oe aaa 40m " =<br>ws TA, , ex 27<br>U ye<br>? J<br>Corporate Governance (Domestic SOEs only) By sector (contestability degree) Domestic SOEs<br>Number Domestic SOEs % SOEs corporatized Distribution of domestic SOEs by Distribution of SOE employment<br>om, I contestability contestability<br>B Dwecty Owned MM inarecty Owned —Crcate Stover Latvia Evtoras i& CompotitiveContestapie [Natural Monopoly 1© CompetitiveContestapie Ml Natural Monopoly<br><!-- End of picture text --> <!-- Start of picture text --> SOEs financial performance<br>% of SOEs operating"<with profittoss<br>1 SOEs operating with profits<br>B® MissingSOEs operatingprofit datawith losses<br>=<br>Domestic SOE profitoss<br>(SOE reporting data)<br>g 1,000,000<br>| 500,000<br>2 SSS<br>Profit O68 Neo’<br><!-- End of picture text -->

<!-- Start of picture text --> SOEs by government participationa<br>Distribution of SOEs byWe government participation<br>-<br>BB Majonty-owned (>50%) I Minority-owned 25-50% [i Minority-owned 10-25% fl Missing<br><!-- End of picture text --> <!-- Start of picture text --> Municipal vs National SOEs<br>[43%]<br>[Bx]<br>+ Municipal ~ National<br><!-- End of picture text -->
**<mark>Table 2. Frequency of total core nontariff measures in developing countries, 1989–98</mark>**

|**Country**|**1989–94**|**1995–98**|
|---|---|---|
||%|%|
|East Asia and the Pacific (7)|30.1|16.3|
|Latin America and the Caribbean (13)|18.3|8.0|
|Middle East and North Africa (4)|43.8|16.6|
|South Asia (4)|57.0|58.3|
|Sub-Saharan Africa(12)|26.0|10.4|

_<u><mark>Note</mark></u>_ <u><mark>:</mark></u> <mark>Figures in parentheses are the number of countries in each region for which data are available.</mark> _<u><mark>Source</mark></u>_ <u><mark>: World Bank (2001), based on Michalopoulous (1999)</mark></u> Another important dimension of reform has been a sharp reduction in the number of countries using foreign exchange restrictions on current account, and in the average foreign exchange premia. The World Bank (2001) reports that the number of developing countries applying foreign exchange restrictions on current account has fallen sharply. Table 3 shows foreign exchange premia for a range of countries in the 1980s and 1990s. This table highlights two things. Firstly, that average foreign exchange market distortions were enormous in the 1980s, and that these premia in most developing countries, in most regions, have fallen to very low levels. While the simple average foreign exchange rate premium is highest in the Middle East and North Africa, at 46.5 percent, this high rate is almost entirely due to large premia in Algeria and Iran. If these two outliers are excluded, the average rate falls to only 1.4 percent. When Nigeria is excluded, the average premium in Sub-Saharan Africa is less than 10 percent, down from 112 percent in the mid 1980s. Clearly, for most countries, the premia are now small enough to imply that foreign exchange distortions impose relatively small taxes on trade.

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