rafmacalaba/datause-encoder-data huggingface dataset:
Learning from Developing Country Power Market Experiences: The Case of Colombia <!-- Start of picture text --> COP/kWh<br>1,200<br>1,000<br>800<br>600<br>400<br>200<br>0<br>1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9<br>2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br>Average contracts price Pool price<br>Figure 6-4 Comparison of the evolution of contracts and pool price.<br><!-- End of picture text --> Figure 6-4 Comparison of the evolution of contracts and pool price.

Source: Own elaboration based on data collected by the World Bank.

# 6.1.2 Short-term wholesale prices

Short-term wholesale energy prices in Colombia increased by 158% in real terms from 2005 to 2016. Prices rose from 32 USD/MWh in 2005 to 100 USD/MWh in 2016, but then fell to 37 USD/MWh in 2017 (in nominal USD). The evolution of prices (see Table 6-3) highlights an upward trend of pool prices since 2011 due to low hydro inflows (XM, 2013, 2014, 2015); and price spikes that occurred during 2009-10 and 201516 due to El Niño phenomena. The monthly pool price is depicted in Figure 6-5. It is worth noting that prices fell in 2017 due to normal hydrological inflows (compared to the very low inflows seen during 2016), and also slow demand growth (XM, 2017b).

Pool price spikes occurred during 2009-10, and even more severe price spikes during 2015-2016, primarily due to reduced hydro availability because of El Niño climatic phenomena (see Table 6-3 and Figure 6-5, in nominal COP/kWh). It has been argued that pool price spikes in 2015-16 were more severe than price spikes during 2009-10, despite similarly low water availability, due to the increased incentives and ability of Gencos to exercise unilateral market power under the Reliability Payment Mechanism (Mcrae & Wolak, 2016). However, exercise of market power has not been proven nor prosecuted in the Colombian power market following the recent pool price spikes.

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substantial fixed cost to collect data for each new user country that is added to the database. Given the leniency allowed by the WTO’s Agreement on Antidumping, there is substantial heterogeneity across countries as to how national laws are implemented and investigations proceed – i.e., each new user country is free to implement its antidumping law and investigative process as it sees fit, provided it is generally consistent with a basic set of principles under the WTO’s Agreement on Antidumping.<sup>8</sup> Thus there are a number of different administrative approaches that each new user country could take.

Second, the WTO imposes only a minimal reporting requirement on member countries’ use of the policy instrument which is insufficient from a research perspective.<sup>9</sup> While the WTO collects information on AD investigation initiations and measures imposed, it does not appear to systematically collect, organize and publicize data on the actual products (HS codes) under investigation, the dates of preliminary and final decisions and imposition of measures, or the names of firms involved in the investigations. This is the minimal amount of information required for empirical economic researchers to accurately match up AD case information with independently-generated data series on trade flows and other economic activity that is critical to assessing the impact of AD.

Thus, the data that we have collected for each of the countries described in section 2 goes beyond what the WTO has made available. Whenever possible, our data derive from original source, national government publications located primarily on domestic government websites, where a number of countries have quite detailed information available. Nevertheless, in a number of instances important elements of the data were only available in hard copy at government depositories in national capitals. For these countries, we dispatched research assistants to these localities to collect the data.<sup>10</sup>

> 8 One reason why the WTO’s Agreement on Antidumping is so lenient is likely because of pre-existing variation in how antidumping was administered by the “old users” who did not want to have too much of their existing procedure changed. For example, Canada’s antidumping law was first enacted in 1904, Australia’s was enacted in 1906, etc.

> 9 See for example the WTO’s website “Notifications under the agreement on implementation of Article VI of GATT 1994” at <u>http://www.wto.org/english/tratop_e/adp_e/antidum3_e.htm</u> , last accessed on 20 August 2005.

> 10 This resulted in an additional fixed cost of finding and training new research assistance with the language skills and in the (physical) geographic location to translate original source information into our data base.

5
industry, and region—collected data for Egypt in 2004, 2007, 2008, 2013, 2016, and 2020. Each survey year is representative of the business environment that year. Of these, this analysis will focus on a panel of 198 firms in 2013, 2016, and 2020. See Table 2 for mean values of our main variables.<sup>9</sup> We supplement the ES data with information on the universe of firms captured by the 2017 Census of Establishments in Egypt and with data from the United Nations International Trade Statistics Database (UN COMTRADE), specifically information on world imports from Egypt over the period of study.

# **_4.2 Stylized Facts of Egypt_**

# **_a. Exporter Characteristics_**

We begin the data analysis at the aggregate level, by comparing total Egyptian exports from the ES with world imports from Egypt from UN COMTRADE. As Figure 5 shows, the ES data represent a reasonable proxy for Egypt’s exports to the world. In 2020, wood manufacturing (ISIC=20) and vehicle manufacturing (ISIC = 34) stand out as the only two sectors overrepresented in the ES relative to the UN COMTRADE data.

Figure 5 aggregates exports from all ES firms. Looking at the data more closely, we see that few Egyptian firms export, either directly or indirectly (Table 3).<sup>10</sup> In 2020, only 27 of the 198 firms in the panel exported.

# **_b. Cross Section_**

As Figure 6 shows, exporters tend to be significantly larger than non-exporters in every year of the survey. In 2020, the average employment size for exporters is 363, statistically different

> 9 Appendix A reports descriptive statistics for firms that survived between 2016 and 2020 with those that did not. Overall, the firms in both groups are broadly similar except in terms of size. Larger firms are more likely to survive. 10 Firms exporting directly are those that sell to other countries without intermediaries. Firms exporting indirectly are those which sell to a wholesaler or other who then resells to customers in other countries.

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Vignette 4 assesses knowledge on identification and treatment of malnutrition among children. The clinical history included asking the mother and child’s name, the age of the child, chief complaint, assessing history of vomiting, convulsions, difficulty breathing, diarrhea, and inquiring about feeding frequency, food variety, vitamin A supplement, micronutrient supplementation, and deworming. The recommended set of physician examinations for the standardized case included measurement of weight, height and mid-upper arm circumference, comparison against growth charts, breastfeeding/drinking, temperature, lethargy, breathing rate, respiratory distress, wheezing, edema on feet, skin pallor, feeding, and running blood tests and parasite screens.

Vignettes 5 and 6 presented an adult standardized patient which tested provider ability to correctly assess high blood pressure and calculate cardiovascular risk. Clinical history included asking the patient’s age, more detail on the chief complaint, symptom onset period, history of nausea, vomiting, oliguria, visual aura during headache, chest pain; inquire about the patient’s smoking status, alcohol intake, family history of heart disease and stroke, diabetes status, lifestyle and physical activity, food intake, weight change, and whether the patient is currently taking antihypertensives or other medications. The physical examination items included the measurement of vitals (blood pressure, weight and height, pulse), and ordering of urine (specifically creatinine ratio and hematuria) and blood tests (specifically for plasma glucose, electrolytes, creatinine, filtration rate, cholesterol) and an electrocardiogram. The provider was then given the necessary information to calculate the cardiovascular risk. The items for Vignettes 5 and 6 were nearly identical; Vignette 6 did not include a clinical history item asking about weight gain.

# Wealth Index

The wealth index estimates the living standard of the household or patients, relative to the living standard of the other households in the sample. In this study, the wealth index for households was calculated by an index using self-reported data including consumer item ownership, amount and value of owned land, the value of rentals, household infrastructure, the source of water, heating, and electricity, and number household members per room. The resulting index is calculated from the standardized first component of principal component analysis, apportioned into quintiles. This method is also used by the Demographic and Health Survey; however, results will differ as the population in this survey is entirely rural. The wealth index was used as a covariate in the household survey indicator regressions.

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# 1. EXECUTIVE SUMMARY

## Background

in Mexico, the cohmnitmen **t** o and reform Is enshrined kI the 1917 Constitution and the reform remains, to this day, an kmportant politieal symbol By 1988, no less than 54 percent of national territory had been affected by the land reform. The land reform peaked In Intensity during the C6rdenas administration (135-40) and, since the mid-1970s, there has beon a significant drop In the amount of land redistrlbuted. Slnce 1977 governments have often stated that there Is no more lnd available to redistrlbute; emphasis has shifted from redlstrbutlon to ensurig that landholders (both within and outside the ejido sector) have adequate legal title to their land. Although expansion of the land reform sector Is not part of the present government's policy agenda, It derives a significant proportion of Its electoral support from the ejido population. Some have argued that the ejido system has always been of greater Importance as a polltical control mechanism than as a tool of economic policy. In any event, the ejldo's political signlficance should not be underestimated.

## Approach

Consideration focusses on Individual ejldos since these constitute the majority; collective ejidos are few In number and, since the mid-1 970s, no govemment has promoted collectivizatlon. An attempt Is made to compare the performance of Individual farms Inside the ejido with comparably-sized private farms. in Mexico, large farm enterprises have traditionally been favoured by government programmes of subsidized Input delivery. Therefore, In reviewing the historical evidence concerning the relative efficiency of ejidos and private farms It Is important to control for the scale of enterprise.

Wherever possible a comparison Is made between ejido parcels of up to 5 hectares and private farms In the same size range. According to the latest agricultural census data (1981), roughly 60 percent of the farms In both tenure categories are of this size. Of the land In holdings up to five hectares, 75 pereont Is controlled by ejidos and 25 percent by private farms; the average size of farms In the private sector Is 74 hectares, compared to 7 hectares In the ejido sector.

# Data Limitations

Comparisons of the performance of both tenure categories are hampered by the Incompleteness of the 1981 census data; In many cases (e.g. when comparing crop yields) the most recent data derive from the 1970 census. Therefore, It Is impossible to draw hard and fast conclusions about the relative productivity of private farms and ejidos in the recent period. However, by observing differences In the Institutional arrangements confronting Individual ejidos and private farms It Is possible to Infer whether such differences are likely to lead to variations In productivity between the two tenure categories.
impose trade restrictions against those trading partners that are experiencing negative demand shocks in their own markets.<sup>7</sup> Finally, Knetter and Prusa (2003) develop a stylized model of pricing behavior in a market with imperfect competition. Their focus is on understanding how international rules regarding dumping, i.e. pricing below average cost, are impacted by exchange rate fluctuations. In their model of a foreign firm that prices to market, an appreciation of the domestic currency leads to a decline in the foreign firm’s marginal cost in terms of the importing country’s domestic currency. At the same time, pricing to market under imperfect competition implies a relatively smaller decline in the domestic currency price of the foreign good. Thus, the foreign firm will simultaneously increase its sales in the domestic market (increasing the likelihood of injury to the domestic import-competing industry) and be less likely to be guilty of dumping. Because an exchange rate movement has opposite effects on the two criteria for dumping, the model gives ambiguous empirical predictions regarding the relationship between an exchange rate appreciation and new antidumping import restrictions.<sup>8</sup> In summary, the literature on macroeconomic fluctuations suggests that temporary trade barriers increase when domestic macroeconomic conditions are weak (Bagwell and Staiger, 2003) and foreign macroeconomic conditions are weak (Bagwell and Staiger, 2003; Crowley, 2010). An appreciation of the domestic currency relative to a trading partner’s currency implies more import restrictions if a national authority’s antidumping investigation places more weight on the criterion of injury to the domestic industry than it places on the criterion of dumping (Knetter and Prusa, 2003).

# **2.2 Empirical model**

This section presents an empirical model of the determinants of the number of imported products from a particular trading partner that a policy-imposing economy subjects to new temporary trade barrier investigations. The model relates the number of products under an antidumping, global safeguard, China safeguard, or countervailing duty investigation in a given quarter to the first lag

> 7 Crowley (2011) examines US antidumping data for industries over 1980-2001 and finds evidence in support of this theory at the relatively disaggregated level.

> 8 While Knetter and Prusa (2003) acknowledge the ambiguous theoretical predictions of their model, they find strong empirical evidence at the annual frequency for 1980-1998 linking exchange rate appreciations to aggregated counts of antidumping filings for a sample that includes data from the US, EU, Australia and Canada.

7
15 the poor.<sup>18</sup> Birdsall and James (1990) note that many governments persist in patterns of spending for health and other social programs despite this lack of tradeoff, apparently because the current pattern better serves those with political power and influence. They also note that alterations in that apparent equilibrium have and do occur; for example in response to exogenous shocks to the political system, or new information from outside the system. Recent analyses in a few countries of the effects of macroeconomic adjustment (or lack of adjustment) on health outcomes provide a start in this area, since they involve study of changes in expenditures patterns as a function of a kind of exogenous shock to the system (in this case changes in the macroeconomic environmenc.19 Finally, work on the optimal ratio between curative and preventive interventions, and the optimal allocation of responsibility for coverage of each between the public purse (e.g. funded by general revenues or nation-wide insurance mechanisms) and the private purse, would provide a benchmark for normative judgments about overall patterns of public spending on health. In spite of the near-consensus that preventive care receives inadequate public spending (and inadequate private spending as well), it is clear that some curative care must be provided (well beyond that portion of curative care which has high externalities, such as care of tubercular patients), and even financed publicly. For example, in a practical sense, it may be difficult to convince consumers to use preventive care if needed referrals to adequate 18 See for example, World Bank (1986) on education spending and World Bank (1987) on health spending.

19 Best known are those sponsored by UNICEF. Behrman (1988) and Pan American Health Organization (1989), who conclude that the impact of the macroeconomic crisis on health care and health outcomes has not been great.
argued that they are given by social norms that limit females’ outside labor market participation, while men are engaged in energy-intensive labor market activities. Thus, few women are engaged in plowing in India, while in Bangladesh no women are observed to pull rickshaw<sup>10</sup> . As a consequence of gender-segregated occupations, as PRH demonstrated, health endowment in the labor market matters only for males. Behrman and Deolalikar (1989) and Sahn and Alderman (1988) also find that health and calorie consumption have significant positive effects on men’s but not on women’s wage rates. So for females, I estimate the technology without differentiating them based on the energy-intensity of their occupation. Moreover, consistent with PRH assumption, there are only a very few females engaged in high energy intensive occupations in the data (see Section 5). Thus, for each of these three categories, I estimate the following health technology function using IFE: where household characteristic vector, **Xhjst** , includes monthly per capita expenditure and its square, per capita household landholding, and household size, all in logs, share of different demographic composition of the household, _Rt_ are survey round dummies to control for any potential seasonal effects on health outcomes, and ∆indicates deviation of an individual’s observation in a given round from its mean (over four rounds). In estimating equation 9 for females, I also include pregnancy and lactating dummies.

Applying IFE estimates of the parameters for calorie intake, age and its square, and household characteristics from equation 9 to the individual data of the corresponding variables, I obtain ˆ estimated log weight for height ( _ln_ ( _h_ )) for each individual who belongs to any of the three above sex-occupation categories. Deducting this estimated value from the observed value of log weight for height ( _lnh_ ) yields a health measurement that includes an individual’s unobserved health endowment ( _μ_ ) and an aggregate unmeasured effect of time-invariant household characteristics ( _ρ_ ) (e.g. the effect of spouses’ characteristics, such as education, assets, unobserved preferences, household landholding, short-run time-invariant living and hygiene conditions, drinking water source, etc. as discussed above):

> time-varying occupation data, I could obtain consistent estimate of its impact on health using IFE without this assumption.

> 10Morris (1997) finds that traditions in Bangladesh often inhibit a woman’s ability to obtain employment outside of home. Purdah, or female seclusion, is an Islamic tradition routinely practiced in Bangladesh among the Muslim majority, which limits women’s labor market participation.

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**Table 4. Predicted infant and under-five mortality rates**

||_Mortal_<br>|_ityrates_<br>|<br>|_Ra_<br>|_tesexpresse_<br>_estimat_<br>|_das per_<br>_edvalue_<br>|_centof_<br>_s_<br>|
|---|---|---|---|---|---|---|---|
||_993_|_1_|_998_|_1_|_993_||_1998_|
|_Poor_|_Nonpoor_|_Poor_|_Nonpoor_|_Poor_|_Nonpoor_|_Poor_|_Nonpoor_|
|_EstimatesfromVLSS_||||||||
|IMR<br>38.50|32.30|36.90|21.80|||||
|U5MR<br>55.90|49.10|51.10|31.40|||||
|_ModelinTable3_||||||||
|IMR<br>34.30|35.20|34.60|23.36|89%|109%|94%|107%|
|U5MR<br>49.76|51.06|50.19|33.97|89%|104%|98%|108%|
|_ModelasinTable3 butno _|_yearintera_|_ctions_||||||
|IMR<br>32.99|32.52|37.34|26.58|86%|101%|101%|122%|
|U5MR<br>47.86|47.18|54.12|38.62|86%|96%|106%|123%|
|_Modelwithseparateregres_|_sionsforea_|_chyear _|_andpoverty_|_group_||||
|IMR<br>35.45|34.10|24.02|24.07|92%|106%|65%|110%|
|U5MR<br>51.14|50.45|35.53|33.94|91%|103%|70%|108%|

# **_Decomposition results_**

Table 5 shows how the various determinants of child survival have changed over time for the "poor" and "nonpoor." Some of these changes reflect sampling variability. Some households were in the 1993 VLSS but not in the 1998 VLSS, and vice versa. Children over the age of five in the 1993 VLSS would have been excluded from our 1998 sample of births even if they had been in the 1998 VLSS sample because they would have been too old in 1998 for our ten-year window. Furthermore, in 40 percent of households in both VLSS samples, a different woman was randomly selected for the fertility questions, so the children (and their mothers) selected for the survival analysis in many "panel" households were different. Some inconsistencies in responses among the panel households are also evident, and we have not attempted to "correct" them. Some people reported a lower completion schooling grade in 1998 than in 1993, and some households reported worse sanitation in 1998 than in 1993. The socioeconomic profiles of the various regions have changed over time. Equivalent consumption in households with small children has risen for both the "poor" and "nonpoor," but in the poorest quartile the percentage increase has been marginally smaller than in the richest three quartiles (24 compared to 28 percent). In the poorest quartile, the data imply a decline in the average years of maternal schooling among families with small children, though the comments above need to be borne in mind. The proportions of poor and nonpoor households with satisfactory drinking water have increased, but the increase has been 20
# FIGURE 3 Evolution of potential growth

## A. Potential growth

<!-- Start of picture text --> Percent<br>Potential growth<br>8<br>Actual growth<br>6<br>2000-2021 potential growth<br>4<br>2<br>0<br>World AEs EMDEs<br>C. Per capita potential growth<br>Percent<br>6 Potential growth<br>Actual growth<br>4<br>2000-2021 potential growth<br>2<br>0<br>World AEs EMDEs<br>2000-10 2011-21 2000-10 2011-21 2000-10 2011-21<br>2000-10 2011-21 2000-10 2011-21 2000-10 2011-21<br><!-- End of picture text --> B. Share of economies and GDP with potential growth below 2000-10 average, 2011-21 <!-- Start of picture text --> Percent<br>100<br>80<br>60<br>40<br>20<br>0<br>World Advanced EMDEs<br>economies<br><!-- End of picture text -->

- D. Global potential growth

<!-- Start of picture text --> Percent 2000-10 2011-21<br>5<br>4<br>3<br>2<br>1<br>0<br>PF MVF UVF For. UCM<br><!-- End of picture text --> Sources: World Bank, UN population statistics.

Note: AEs = advanced economies; EMDEs = emerging market and developing economies. A.B.C. Based on potential growth derived using production function approach. GDP-weighted average. Sample includes 30 advanced and 53 emerging market and developing economies.

B. Number of economies and their share of global or group GDP with potential growth in each period below its 2000-10 average. Horizontal line indicates 50 percent. Unbalanced sample of 30 advanced economies and 53 EMDEs for 2000-21.

D. Based on common sample of 30 advanced economies and 25 EMDEs for 2000-21 to ensure consistency in samples across methodologies. Orange whiskers indicate range implied by GDP-weighted average of country-specific standard deviations of potential growth estimates for each approach.

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