rafmacalaba/datause-encoder-data huggingface dataset:
Another significant cost to the firm comes from legal fees. All securities issues must be presented as a legal document, including a prospectus and/or offering memorandum. A firm engages outside legal counsel specializing in issuance, in addition to the internal legal team which usually is responsible for all background work. If the firm is issuing internationally, the legal costs are multiple times higher, as the firm must hire both domestic and international lawyers in order to comply with both sets of law.

In most countries a firm must be registered with the supervisory body prior to any issuance. The majority of firms considering issuance have become registered firms well before commencing an issuing process. In permitting a company to register, the regulatory body in each country has its own requirements pertaining to audited accounting statements, information publication, etc. When registering a specific security issue, the firm must pay the regulator a fee almost always based on issue size and issue type. In some countries the regulator also orders a technical study to be performed (at the company’s cost), of the company and issue, which will be made available to the public. Finally, some regulations require the company to hire either a trustee or a bondholder representative to act on behalf of the security holders.

Either regulations or customary practice require credit ratings. The number and source of ratings required depends on the country and the nature of the investor. For example, market regulators may require a firm to engage one domestic rating, while institutional investor regulators (like pension funds) may require an issue to have two independent ratings from international rating agencies to be considered a valid investment. Consequently, in practice, the firm may need to pay for two ratings in order to reach a target investor base even though regulations do not mandate them.

Most firms wish to have their securities listed and traded on a stock exchange, which will charge its own fees based on security type and size. The firm must also pay a depository fee if there is a central depository facility available.

Finally, the firm will incur marketing and publishing costs. Some forms of publishing are forced by law, and give the company a minimum standard for creating public awareness. For marketing purposes, the company will have to print prospectuses and offering memorandum to deliver to potential clients. Finally, the company bears the costs of any road shows, either domestic or international, used to market the deal.

# **B.  Methodology**

The cost data was gathered from a combination of web site searches of stock exchanges and regulatory bodies, security information from Bloomberg and Bondware, and heavily relied on interviews with securities lawyers, investment bankers, regulators, and companies themselves (typically the CFO). The process itself, when applied across countries, helped to formulate a questionnaire to be followed in the interviews.<sup>2</sup>

> 2 This questionnaire is available from the author on request.

4
Where there is more than one observation. on unemployment for a particular country, only the latest date is used. The unemployment data used in the group aggregations and the size of the working age population used for weighting are presented Table 2'.

# 2.3. The sectoral distribution **of** the work **force**

Sectoral distribution data are also compiled from a variety of sources. First, and most importantly, is the ILO's _Yearbook of Labor Statistics_ data. Data from Table 2-A of the Yearbook -which reports census survey, labor force survey, household survey, and official estimates- was downloaded from the World Bank's BESD on-line database. Only the last observation in the 1980-93 period is used for each country. The data give the number of workers in each of 10 industry categories which are aggregated as follows:

## * Agriculture: Agriculture

- Industry: Mining and Quarrying; Manufacturing; Gas, Electricity and WN'ater; Construction

- Services: Trade; Transport; Banking; Commercial Services; Not Adequately Defined or Described

Second, these data supplemented with ILO estimates for the distribution of the wvork force across the three sectors in 1990 for a variety of countries in all regions except Latin America and the Caribbean<sup>4</sup> - these are recent (current as of May 1995) estimates for 1990.

> 31n Table 2 there are several countries in East and Central Asia (marked with an asterisk) with working age population data not present in Table 1 . These data are derived from a recent update from the ILO which reports decennial population estimates until 1990 for these new countries. A 1995 projection is made by applying the 1980-90 annual average growth rate of the working age population to the 1990 size of the working age population.

> 4 Estimates dor Latin America and the Caribbean are said to be forthcoming.

5
# PAYING THE PRICE FOR UNRELIABLE POWER SUPPLIES: GENERATION OF ELECTRICITY BY PRIVATE FIRMS IN AFRICA

Other characteristics also affect the likelihood that a firm will choose to generate its own electricity. Size is one such characteristic. Larger firms are more likely to have their own generator and are more likely to have a generator of high capacity. Around half of medium size and large firms (those with 50 or more employees) have their own generator, compared with just 10 percent of small firms and micro enterprises (less than 10 employees) (figure 20). The average capacity of the generators used by small firms is about one-third of those used by enterprises of medium size (10 to 100 employees) and one-quarter of those used by large enterprises (more than 100 employees).

**Figure 19 Generator ownership by firms and share of electricity generated in-house, by frequency of power outages**

<!-- Start of picture text --> 0.6 14.00<br>0.5 12.00<br>10.00<br>0.4<br>8.00<br>0.3<br>6.00<br>0.2<br>4.00<br>0.1 2.00<br>0 0.00<br>< 5 days 5 - 15 days 15 - 60 days 60 - 120 days >120 days<br>Generator Ownership (% of Firms)<br>Percentage of electricity from own or shared generator<br><!-- End of picture text --> Source: World Bank, Enterprise Survey Database.

**Figure 20 Generator ownership, by firm size**

**Figure 21 Probability of having a generator, by industry**

Source: World Bank, Enterprise Survey Database.

14
Table S12. Relationship Between Inequality and Human Capital (Current and Lagged Inequality)

|Dependent Variable is:|Share of|Population Tertiary Education|
|---|---|---|
||(1)|(2)<br>(3)|
|Inequality Variable is:|Gini<br>Brueckner et al. (2015)|Net Gini<br>Solt (2015)<br>Market Gini<br>Solt (2015)|
|Inequalityit|1.10**<br>(0.55)|2.66**<br>(1.31)<br>1.37**<br>(0.62)|
|Inequalityit-1|1.00<br>(0.86)|3.41***<br>(1.22)<br>2.00***<br>(0.73)|
|Inequalityit|-0.17**|-0.39**<br>-0.19**|
|*ln(yi1970)|(0.08)|(0.20)<br>(0.09)|
|Inequalityit-1|-0.14|-0.52***<br>-0.28**|
|*ln(yi1970)|(0.12)|(0.19)<br>(0.11)|
|Kleibergen Paap F-Statistic|9|12<br>17|
|Country FE|Yes|Yes<br>Yes|
|Time FE|Yes|Yes<br>Yes|
|Observations|361|592<br>592|

Note: The method of estimation is two-stage least squares. Bootstrapped standard errors are shown in parentheses. The endogenous variables are _Inequalityit_ and _Inequalityit-1_ ; the instruments are _Residual Inequalityit_ and _Residual Inequalityit-1_ . _Residual Inequalityit = Inequalityit – αln(yit)_ , where α measures the effect that ln(yit) has on _Inequalityit_ . *Significantly different from zero at the 10 percent significance level, ** 5 percent significance level, *** 1 percent significance level.

56
Various authors (Brown et al., 1992; Levy and Van Wijnbergen, 1995; Veeman et al., 2002) have analyzed the regional effects of agriculture sector liberalization. Some regions of Mexico, mostly in the north, already had experienced enormous growth in agricultural productivity for several decades following World War II, based on large investments in irrigation and mechanization and the introduction of fertilizers, while the center and the south have been characterized by small plots, limited capital investment, subsistence production, and income supplementation by seasonal work on commercial farms. After liberalization of the agricultural sector, the southern peasants have been hit by the elimination of protection on the products they traditionally concentrate on, as for example maize, while the northern agricultural activities could benefit from opening markets for products for which Mexico holds a comparative advantage, such as fresh fruits and vegetables.

Equivel and Messmacher (2002) argue that the divergent process of the 1990s was mostly driven by the divergence observed in labor productivity associated with education and infrastructure, while Harrison and Hanson (1999) find an increase in the relative wage of skilled workers after Mexico’s trade liberalization, where foreign direct investment, export orientation and technological change played an important role.

# **b) Descriptive Data**

# **b.1)  Growth in Mexico**

Figure 2 displays the evolution of GDP per capita in Mexico since 1960 and distinguishes between three different phases. The first period started in 1930 and lasted until the end of the 1970s and is called the “Mexican Miracle” because of a long time of economic growth, spurred by a model of import substitution industrialization (ISI), which protected and promoted the development of national industries. The second period from 1981 to 1995 is called the “the lost decade and a half”, because of its negative average GDP per capita growth, caused by two economic crises (in 1981/82 and 1994/95). Finally, there is a third “post-crisis” growth period that extended up until last year’s external shocks.

**Figure 2: GDP per capita (constant Mexican Pesos), 1960 – 2007**

<!-- Start of picture text --> 20000<br>18000<br>16000<br>14000<br>12000<br>10000<br>8000<br>6000<br>4000<br>2000<br>0<br>GDP per capita (constant Mexican Pesos)<br><!-- End of picture text --> Source: Elaborated with data from the World Development Indicators 6
- ILO (2018). India wage report: Wage policies for decent work and inclusive growth. Technical Report. International Labor Organization.

- Jaynes, E.T. (1957). Information theory and statistical mechanics. _Physical review_ , **106.4,** number 620.

- Kijima, Yoko and Lanjouw, Peter (2005). Economic diversification and poverty in rural india. _Indian Journal of Labour Economics_ , **48,** number 2.

- Kolenikov, Stanislav (2014). Calibrating survey data using iterative proportional fitting (raking). _The Stata Journal_ , **14,** 22–59.

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- Mehrotra, Santosh and Parida, Jajati Keshari (2021). Poverty in india is on the rise again. Blog. The Hindu.

- Newhouse, David Locke and Vyas, Pallavi (2019). Estimating poverty in india without expenditure data: A survey-to-survey imputation approach. Policy Research Working Paper 8878. The World Bank.

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- Pinkovskiy, Maxim and Sala-i Martin, Xavier (2016). Lights, camera income! illuminating the national accounts-household surveys debate. _Quarterly Journal of Economics_ , **131,** 579–631.

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68
**Table 4.1 Allocation of national pension system assets by infrastructure sector**

Year-end 2006 or most recent available; US$ millions

|Country|Total<br>pension<br>assets|Total pension<br>assets<br>invested in<br>infrastructure||
|---|---|---|---|
||US$|millions|Sector and type of funds, where known|
|Benin|125|—||
|Cape Verde|170|22.5|Telecoms equities (19.1) and electrical utility<br>bonds (3.4)|
|Chad|n.a.|0||
|Congo, Dem.<br>Rep.|n.a.|0||
|Ghana|1,076.7|0||
|Kenya|1,770.3|—||
|Madagascar|62.4|—||
|Malawi|—|0||
|Namibia|3312|—||
|Niger|79|—||
|Nigeria|3,507.8|0||
|Rwanda|132.7|—||
|South Africa|80,202.3|—||
|Tanzania /c|578|0.4|Feasibility study of Kigamboni Bridge|
|Uganda|470.6|8.6|Telecoms and EADB bonds /a|
|Zambia|314.1|0||
|Total|91,800.5|32||
|Chile /b|88,293.5|7,393||
|Malaysia|69,659.0|—||

Sources: Pension system asset data sourced from national pension funds and financial authorities; Axco country reports.

Note: Total pension assets are underestimated for several countries because national authorities do not compile data covering all funds (in some cases due to inadequate regulation of the sector). Pension funds assets data are for 2006 with the exception of Benin (2004), Cape Verde (July 2007), South Africa (2004), Rwanda (2005), Namibia (2004), Tanzania (June 2007 for National Social Security Fund), Uganda (June 2007), Madagascar (2005), Niger (April 2007), Nigeria (August 2007), Zambia (March 2007), and Chile (July 2007). Data breakdown not available for Benin, Burkina Faso, Cameroon, Côte d’Ivoire, Ethiopia, Lesotho, Mozambique, Namibia, Niger, Rwanda, Senegal, South Africa, and Sudan.

a. East African Development Bank (EADB) provides development finance within the East African Community (EAC) to projects in sectors including agriculture, transport and communication, construction and manufacturing, electricity, water supply, and housing.

b. Chilean authorities were unable to specify the pension system’s asset allocation specifically in infrastructure sectors but given that corporate bonds issued for financing infrastructure development as a share of total (excluding nondomestically issued as well as bank bonds and securitized) is 48 percent and domestically issued equity issued by firms in infrastructure sectors accounts for 27 percent of total market cap, one can roughly estimate that up to $3.3 billion of pension fund asset holdings were in corporate bonds issued by companies/projects in infrastructure sectors; and around $4 billion can be estimated as holdings in domestically issued equity issued by infrastructure companies/projects.

— = Not available; n.a. = Not applicable.

29
**Survey and settlement:** Rather than responding to any specific land transaction, the survey and settlement process recognises all land transfers that have occurred since the previous revisional survey but remain unrecorded for various reasons. The Director, Land Records and Survey (DLRS) is the nodal officer responsible monitoring the survey and settlement operations and preparation of an up-to-date Record of Rights (ROR). Survey and settlement operations are organised through Settlement Officers in charge of respective settlement zones (with each zone covering several districts), and Charge Officers covering a 'range' or 'circle' across more than one district.

**Land registration:** The government's response to current land transfers<sup>1</sup> I is organised by the Inspector General of Registration-cum-Excise Commissioner (IGR) who deals with registration and excise matters through District Registrars/Sub-Registrars and Excise Superintendents. All policy matters relating to registration administration and stamp duty are submitted by the IGR to the Government. Under section 69 of the Registration Act, the IGR is responsible for general supervision over all registration offices in the state and shall have the power from time to time to make rules consistent with the Act. Three Deputy IGRs are in charge of the ranges: Northern Range at Sambalpur, Central Range at Cuttack, and Southern Range at Berhampur. They have the power to inspect all registration offices falling within their ranges. At the district level, the District Registrar is empowered under section 68 of the Registration Act to supervise the sub-registrars under him. The ADM (General) usually functions as the District Registrar with the support of a District SubRegistrar. There are 144 sub-registration offices in Orissa. The Sub-Registrars, District Sub-Registrars and Deputy IGRs have been deemed to act in place of the Collector for the disposal of under-valuation cases under section 2(9) of the Stamp Act.

**Land consolidation:** The Director, Consolidation controls and monitors land consolidation operations in the state. The field units of the consolidation division are organised in a similar manner to the settlement division with Consolidation Officer (for a zone) and Assistant Consolidation Officers (for ranges within a zone).

In the field, the District Collector (DC) is the superior authority for revenue administration in the district, and the district-level officers of different divisions of the BOR (e.g. the Assistant Settlement Officer, Assistant Consolidation Officer and the District Registrar) report to the DC on administrative issues. However, the BOR also has a judicial role which is exercised through these field officers. Thus, the latter report to the RDC of their respective zones on judicial matters. The District Collector supervises the Sub-collectors (at the blocklevel), Tehsildars (in charge of a tehsil) and the Revenue Inspectors (RIs, or _patwaris)_ who cover a number of villages within the revenue circle.

10 For present purposes, land transfers refer to transfers through sale, gift, and inheritance.

20
**Fig. 1: GDP in OECD countries**

<!-- Start of picture text --> 105%<br>100%<br>95%<br>90%<br>85%<br>80%<br>75%<br>75% 80% 85% 90% 95% 100% 105%<br>Q2-2020 GDP as % of GDP Q4-2019<br>Q3-2020 Q4-2020<br>% of Q4-2019<br><!-- End of picture text --> Source: OECDstats.

20%. Along the vertical axis, the speed of the recovery in the third and the fourth quarter is measured by the distance between each point and the 45<sup>_◦_</sup> degree line (no recovery) and the 100% (full recovery) line. For example, the United States and New Zealand had a similar reduction of GDP in the second quarter of 2020, 10% relative to the pre-pandemic quarterly GDP, but the recovery was different. New Zealand’s output was 103% and 101% of the fourth quarter of 2019 GDP in the third and fourth quarters of 2020, respectively, while the corresponding numbers for the United States were 97% and 98%. Table 2 in Appendix A has the data underlying Figure 1.

In our model, we take the size of the shutdown as an unanticipated shock, which determines the fall in GDP during the lockdown. We are interested in characterizing the speed of the recovery.

We find the cases of the United States and New Zealand of particular interest. The US is our calibration benchmark and we assess the quantitative implications of our laboratory economy using the US data. Our interest in New Zealand, in turn, lies in the starkness of its containment policies. It implemented a very intense, but brief shutdown in the second quarter of 2020 and, except for some time intervals and locations, lifted mobility restrictions thereafter. In this sense, New Zealand fits very well our benchmark experiment of a one quarter shutdown.<sup>6</sup>

> 6Figure 16 in Appendix B shows, using data from Google mobility reports on visits to shopping venues

4
the aggregate dynamics. Macro‐econometric analysis accounts for all the direct and indirect effects of innovation and therefore gives a fuller picture of aggregate dynamics and employment. However, in macro‐econometric analysis it is difficult to find an appropriate proxy for technological change and these analyses are affected to a larger extent by cyclical conditions, overall labor market dynamics, and other factors that are hard to control for, such as, trends in variables over time (such as working hours) and various institutional elements.

**_Product innovations tend to be more employment creating than process innovations_** _._ Harrison et al (IJIO, 2014) do a firm‐level analysis of process and product innovations for France, Germany, Spain and the United Kingdom during 1998‐2000 and find that while process innovations tend to reduce employment requirements per level of output, the growth of demand for the old products (due to a reduction in their price) and the growth of demand  for new products, together, more than compensated for the reduction in employment. In a study of 16 industries in Germany, Zimmerman (1991), using a long panel data set of German manufacturing firms, finds that  overall unemployment was higher as a result of technical advance in the 1980s. Benavente and Lauterback (2008) using firm‐ level data for manufacturing firms in Chile during 1998‐2001 find that although improvements in productivity diminish employment, the increase in total sales works as a compensation effect, rendering the total effect on employment positive. They conclude that product innovations increase output and employment, particularly if the new goods are not substitutes for existing goods. Alvarez et al (2011), examining the relationship between employment growth and innovation in the manufacturing industry in Chile during 1995‐2007, find that process innovation has statistically ambiguous effects on employment growth, but product innovation is usually positively related to employment growth, regardless of firm size, and in both low and high‐ tech industries. Antonucci and Pianta (2002) find an overall negative impact of technological change on employment in manufacturing industries across four European countries. Evangelista and Savona (2002) find a positive employment effect in the most

13
WPS4162

# **An Analysis of Crop Choice:**

**Adapting to Climate Change in Latin American Farms**<sup>**1**</sup>

Niggol Seo University of Aberdeen Business School, UK and Robert Mendelsohn School of Forestry and Environmental Studies, Yale University, USA

# **Abstract**

This paper explores how Latin American farmers adapt to climate by changing crops. We develop a multinomial choice model of farmer’s choice of crops. Estimating the model across over 2000 farmers in seven countries, we find that both temperature and precipitation affects the crops that Latin American farmers choose. Farmers choose fruits and vegetables in warmer locations and wheat and potatoes in cooler locations. Farms in wetter locations are more likely to grow rice, fruits, and squash and in dryer locations maize and potatoes. Global warming will cause Latin American farmers to switch away from wheat and potatoes towards fruits and vegetables. Predictions of the impact of climate change must reflect not only changes in yields or net revenues per crop but also crop switching.

## World Bank Policy Research Working Paper 4162, March 2007

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 We thank Emilio Ruz, Flavio Avila, Jorge Lozanoff, Luis José María Irias, Magda Aparecida de Lima, César Teherán, Jorge González, Flavio Játiva, Alfredo Albin, Liubka Valentina Trujillo, Luisa Caraballo Silva, and Ariel Dinar for their contributions to this effort.  This project was funded by the Research Committee of the World Bank under the study 'Climate Change and Rural Development' that was tasked managed by Ariel Dinar.

1