rafmacalaba/datause-encoder-data huggingface dataset:
# CLEMENS & TIONGSON

|band-<br>width<br>2_._227<br>1_._406<br>1_._603<br>2_._147<br>3_._276<br>2_._138<br>3_._390<br>2_._103<br>3_._192<br>2_._490<br>1_._873<br>2_._041<br>2_._402<br>4_._436<br>2_._356<br>2_._904|
|---|
|ated effect<br>_p_-val.<br>0_._682<br>_<_0_._001<br>_<_0_._001<br>0_._983<br>0_._802<br>0_._955<br>0_._661<br>0_._528<br>0_._476<br>0_._838<br>0_._489<br>0_._117<br>0_._285<br>0_._993<br>0_._977<br>0_._969<br>evious months.<br>ngular kernel.|
|nt-on-tre<br>s.e.<br>0_._182<br>0_._0854<br>0_._120<br>0_._337<br>1_._627<br>0_._289<br>0_._615<br>0_._133<br>0_._426<br>0_._110<br>0_._235<br>0_._0263<br>0_._0677<br>0_._503<br>0_._0921<br>0_._285<br>ge over 6 pr<br>ect.<br>n(2012), tria|
|Treatme<br>_μs↓_0_−μs↑_0<br>_τs↓_0_−τs↑_0<br>_−_0_._0744<br>0_._838<br>0_._586<br>0_._00716<br>0_._409<br>0_._0163<br>_−_0_._270<br>0_._0840<br>0_._304<br>_−_0_._0225<br>_−_0_._163<br>0_._0412<br>0_._0723<br>0_._00413<br>_−_0_._00262<br>_−_0_._0110<br>er month, avera<br>er on each subj<br>d Kalyanarama|
|effect<br>_p_-val.<br>0_._683<br>_<_0_._001<br>_<_0_._001<br>0_._983<br>0_._804<br>0_._955<br>0_._656<br>0_._526<br>0_._477<br>0_._839<br>0_._493<br>0_._122<br>0_._284<br>0_._993<br>0_._977<br>0_._969<br>ilippine pesos p<br>t decision-mak<br>wingImbens an|
|t-to-treat<br>s.e.<br>0_._0830<br>0_._0541<br>0_._0612<br>0_._157<br>0_._814<br>0_._134<br>0_._505<br>0_._0703<br>0_._226<br>0_._0591<br>0_._133<br>0_._0141<br>0_._0361<br>0_._269<br>0_._0493<br>0_._173<br>ounts in Ph<br>mary or join<br>ction follo|
|Inten<br>_μs↓_0_−μs↑_0<br>_−_0_._0339<br>0_._403<br>0_._281<br>0_._00331<br>0_._202<br>0_._00755<br>_−_0_._225<br>0_._0446<br>0_._161<br>_−_0_._0120<br>_−_0_._0910<br>0_._0218<br>0_._0387<br>0_._00221<br>_−_0_._00140<br>_−_0_._00662<br>_<_65. Money am<br>cant was the pri<br>. Bandwidth sele|
|_μs↑_0<br>0_._833<br>0_._142<br>0_._336<br>)<br>0_._492<br>0_._471<br>0_._251<br>9_._262<br>= 2142)<br>0_._493<br>0_._262<br>0_._232<br>9_._171<br>0_._00730<br>0_._0695<br>11_._03<br>0_._141<br>0_._697<br>ans18⩽Age <br>ether the appli<br>dults_N_=2142<br>r in Korea.|
|Outcome<br>_Applicants only_(_N_ = 875)<br>Worked in past 6 months?<br>Now in Korea?<br>Now abroad?<br>_Applicant’s spouses only_(_N_ = 421<br>Worked in past 6 months?<br>Days worked, previous mo.<br>Any wage income?<br>_ln_wage income<br>_All non-applicant adults only_(_N_ <br>Worked in past 6 months?<br>Days worked, previous mo.<br>Any wage income?<br>_ln_wage income<br>Now in Korea?<br>Now abroad?<br>Years of education<br>Visited health facility past mo.<br>_if so, private facility?_<br>All variables at individual level. ‘Adult’ me<br>‘Decisions’ is an indicator variable for wh<br>For applicants_N_=875, for non-applicant a<br>Treatment = household_ever_ had a membe|

42
I POLICY RESEARCII WORKING PAPER 1263

# Summary findings

Equity flows to developing countries climibed to **an** estimated $13 billion in 1992, four times the amount invested three years earlier. Investment increased partly becauIse countries removed restrictions on foreign ownership, liberalized capital account transactions, and generally made foreign access to their markets easier.

Claessens and Rhee investigate how stock performance in emerging markets is affected by foreign investors' formal access to stocks (as measured by the International Finance Corporation's index of "investability").

To measure foreigners' access to emerging-market stocks, they use the investability index created by the IFC's Emerging Market Data Base. The IFC. indexes should be a good indicator of changes in legal barriers over time or of the relative importance of those barriers across securities in one market at a given point in time, or across markets.

Using the Stehle ( 1977) model, (laessens and Rhee reject the hypothesis that emerging markets are integrated With world capital markets (for most cmergir markets). They fail to reject the hypothesis that cmergin niarkets are segmented (for all emerging markets).

Claessens and Rhee interpret this as legal and other barriers limiting foreign investors' access to emerging markets. They next investigate the relationship between stock performance and the investability index to determine the importance of legal barriers relative to other barriers.

They find a strong relationship between a stock's price-earnings ratio and its investability index, which suggesLs that formal barriers to foreigners' access has a negative effect on stock prices and thus raises the cost of capital for firms listed. Countries could lower the (riskadjusted) cost of capital, they contend, by removing legal barriers to foreign investors' access to equity markets.

This paper - a product of the D)ebt and International Finance Division, International Economics Department - wa prepared for the NBER conference on "IInterrnationalization of Equity Markets," held in San Francisco in October 1993 and will be forthcoimiing in the conference volime puiblished hy the University of C hicago Prcss. C:opics of this paper arc available free fromii the World Bank, lX 18 lH Street NW, W'ashington DC 2043.3. Please contact Fatein Hatah, r oom H8087, extension 35835 (40 pages). March 1994.

_The Policy Research Working Paper Series disseminates tf7e findings of urk in progress to encourage the exRchange of ideas about development issues. An objecti e of the series is to get tfoe findings out quickiy) etlen if the presentations are lPss than fully polished. The papers carry the rnames of the autihors and should be used and cited accordinglv._ **_The_** _findings, interpretations._ **_and_** _conclusions_ **_are_** _the aut/sors 'oun and should not he attributed to the_ **_World Bank,_** _its Ltecutive Board of lDirectors,_ **_(r any_** _of its ,netpn'er countries._ IProduced **bv** the Policy Research Dissemination (Center
structure of the paper and its relationship with the literature. It also applies a standard empirical approach used in the literature for oil markets to corn, to motivate and provide a benchmark for the models. Section 2 presents the low-frequency model and its results. Section 3 presents the high-frequency model, calibration, and estimation results. Section 4 summarizes and concludes.

# 1.1 Literature Review

This paper, therefore, contributes to the literature in three respects: ...rst, it tests the hypothesis that the spike in commodity prices was due to by non fundamental reasons, but focuses on a less explored market, since most of the literature has focused on oil markets. Second, it adds a new feature to high-frequency analysis: information shocks. This paper quanti...es the historical impact of information shocks by incorporating USDA reports as a source of information. Additionally, it estimates private signals and their impact on prices, showing that when it comes to quarterly analysis, they are a relevant source of volatility. Third, it decomposes price changes per source of change— that is, it estimates the impact of each variable change each year, from 1975 to 2015, and therefore o¤ers alternative explanations for the observed change in prices in past years. This also allows to estimate the fraction of prices that cannot be explained by fundamental or information factors, leaving a measured space for further research.

Some papers have already attempted to use competitive models to study these markets. Roberts and Tran (2012) use a competitive model to estimate the role ethanol mandates in corn prices, ...nding they can account for 11 to 0 percent of food price increase between 2005 and 2011. Zhou and Babcock (2017) use a model to estimate the role of hypotheically reducing biofuel mandates on prices. Mallory et al (2012) use this approach to link ethanol and corn markets, ...nding that under certain conditions, future price expectations can in‡uence nearby futures across each other. Tegene et al (1988) make use of this method to estimate long-run price elasticity of corn acreage, ...nding it to be 0.2.

More generally, the literature has also examined whether commodity markets have been altered for non fundamental factors in the past decades, such as ...nancial speculation. For instance, in energy markets results tend to indicate small or null e¤ects of speculation on oil prices. In their canonical paper, Kilian and Murphy (2014) develop a VAR model with speculative demand shocks and contrast it with recent oil inventory data and ...nd no basis for speculation’s being blamed for 6
# **1. INTRODUCTION**

Indigenous peoples make up less than 5 percent of the world’s population (370 million indigenous peoples), yet comprise 15 percent of the world’s poor (UNPFII 2006). Overgeneralizing and drawing on international accords, declarations and policy declarations, it would appear that four things define indigenous peoples (Martínez-Cobo 1986; and ILO Convention 169 of 1989): (i) they are the descendants of the original populations inhabiting their lands at the time of conquest and identify as such; (ii) they speak (or spoke) a distinct and native language, and typically aspire to remain distinct culturally, geographically and institutionally rather than assimilate; (iii) they have an affinity and attachment to the land; and (iv) they tend to maintain distinct social, economic and political institutions within their territories.

Due to the different methods used to identify indigenous peoples, estimates vary greatly. However, a reasonable lower-bound estimate of the indigenous population in Latin America is about 28 million (Hall and Patrinos 2006). It is also true that however defined, indigenous peoples are among the poorest of the poor in any country where they live (Psacharopoulos and Patrinos 1994; Hall and Patrinos 2006). Despite significant changes in poverty rates overall, the proportion of indigenous peoples in the region living in poverty did not change much in most countries from the early 1990s to the early 2000s (see Figure 1).

Figure 1: Poverty for Indigenous and Non-indigenous Peoples, 1990s to early 2000s, by Country <!-- Start of picture text --> 100 100<br>80 80<br>60 60<br>40 40<br>20 20<br>0 0<br>Bolivia Ecuador Guatemala Mexico Peru Bolivia Ecuador Guatemala Mexico Peru<br>Indigenous Early Year Indigenous Last Year Non-indigenous Early Year Non-indigenous Last Year<br><!-- End of picture text --> Source: Hall and Patrinos 2006 Notes: Poverty headcounts are reported for the following years: Bolivia, 1997 and 2002; Ecuador, 1994 and 2003; Guatemala, 1989 and 2000; Mexico, 1992 and 2002; Peru, 1994 and 2000 Previous studies show that being indigenous is associated with being poor, and that over time that relation has stayed constant. Studies also show that indigenous peoples’ poverty has not diminished over time, including over the period of the world’s first indigenous peoples decade, 1994-2004 (Hall and Patrinos 2006). Furthermore, indigenous peoples suffer from many other disadvantages, and even when they are able to accumulate human capital this does not translate into significantly greater earnings or a closing of the poverty gap with the nonindigenous population. This holds for countries where indigenous peoples are a small fraction of the overall population, such as Mexico (Ramirez 2006) and Chile (Hopenhayn 2003), countries where a large portion of the population is indigenous such as in Bolivia (Feiring 2003); in
# **Table 1: Descriptive** **<u>Statistics</u>**

||||||||Level|of Education (|%)|
|---|---|---|---|---|---|---|---|---|---|
|||Wa<br>(rubles c|ge<br>urrent)|<sup>Exper</sup><br>(yea|<sup>ience</sup><br>rs)|<sup>Education</sup><br>(years)|Secondary|Vocational|Higher|
|Year|N<br>|Mean|SD|Mean|SD|Mean SD|Percent|Percent|Percent|
|1994|3204|266012|339748|22.5|10.6|12.4 2.7|21.3|47.8|25.9|
|1995|2792|546812|613490|<br>22.5|10.4|12.5 2.5|21.5|46.1|28.8|
|1996|2355|803429|993793|22.3|10.3|12.6 2.5|19.2|47.1|30.7|
|1998|3186|<br>895|943|<br>22.9|10.2|12.5 2.4|19.3|50.7|27.6|
|2000|3282|1808|2550|22.7|10.3|12.6 2.3|19.9|50.3|27.9|
|2001|3659|<br>2664|2839|<br>22.3|10.1|12.7 2.3|19.5|48.6|30.6|
|2002|3853|3596|4299|22.3|10.2|12.7 2.2|19.1|49.3|30.5|
|2003|3900|<br>4355|4003|<br>22.3|10.2|12.8 2.2|18.9|49.0|31.3|
|2004|3994|5361|4913|22.1|10.3|12.8 2.2|18.3|50.1|31.0|
|2005|3937|<br>6624|5715|<br>22.2|10.5|12.8 2.2|18.3|49.4|31.9|
|2006|4837|8081|6577|22.3|10.5|12.8 2.3|17.9|50.7|30.9|
|2007|4766|<br>9655|7129|<br>22.5|10.6|12.8 2.3|18.4|49.9|31.3|
|2008|4844|12788|10767|22.6|10.8|12.9 2.3|17.8|47.7|34.2|
|2009|4818|<br>13344|10409|<br>22.5|11.0|12.9 2.3|16.6|47.7|35.5|
|2010|7360|14743|12579|22.6|11.1|13.0 2.3|16.9|48.0|34.9|
|2011|7197|<br>16190|12853|<br>22.5|11.1|13.0 2.3|17.9|46.8|35.1|
|2012|7461|18844|15104|22.5|11.2|12.9 2.4|18.2|45.8|35.8|
|2013|7346|<br>20567|16404|<br>22.5|11.2|13.0 2.3|17.0|46.7|36.1|
|2014|6161|22734|17280|22.3|11.1|13.1 2.3|16.5|45.7|37.6|
|2015|6236|<br>23532|16966|<br>22.2|11.2|13.2 2.3|15.2|44.4|40.3|
|2016|6313|24899|18634|22.3|11.1|13.3 2.3|14.6|43.6|41.7|
|2017|6375|<br>26226|19542|<br>22.4|11.0|13.2 2.3|14.0|45.0|40.9|
|2018|6129|28081|19728|22.5|10.8|13.3 2.3|13.8|45.0|41.1|

Source: RLMS The Mincer equation, arguably the most widely used in empirical work, can be used to explain a host of economic phenomena. One such application involves explaining (and estimating) wage earnings as a function of schooling and labor market experience. The Mincer equation provides an estimate of the average monetary returns of one additional year of education. This information is important for policy makers who must decide on education spending, prioritization of schooling levels, and education financing programs such as student loans (Patrinos 2016).

The empirical analysis in this paper presents results for the general working population of the Russian Federation aged 25-64. We use a basic Mincerian specification shown in equation (1): L 0 1 ⋅E E 2 ⋅E 3 ⋅E (1) where LL(WL LLWW) = bb is a logarithm of monthly wage, + bb + bb pp+ bb Epp<sup>2</sup> E+ εε stands for the years of education or highest attained level of education, E and E reflect the years of working experience and its LL(W LLWW) pp pp<sup>2</sup> 7
Figure Al: Capital Flows to Developing Countries ($billion) <!-- Start of picture text --> 300 300 ~~~~~~~~~Aggregate284.6<br>250{<br>200 1 243.8<br>/rivate flo<br>150<br>100.6 ~<br>100<br>50 --44<br>0 1 1 i i 1 1<br>1990 1991 1992 1993 1994 1995 1996<br><!-- End of picture text --> Figure A2: Government Deficit in Developing Countries (weighted average of 20 developing countries' central government deficit % of GDP) <!-- Start of picture text --> 7-<br>1 o- - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - - -<br>0 - - - - - - - - - - - - - - - - - - - -- - - - -- - - - - - - - - - - - - - - - - - -<br>196 18 98 199 19 91 192 19 94 19<br>a~~~~~~~~~~ 4 -- - -- -- - - -- - -- -- - Y- ars-- r -- -- -- -- -- - -- -- -- --- --- -<br>----<br>Weighted----- aver- g of--2-de---loping--countries cen--al--go---rnment<br>2 - - - -- - --- - - -- --- deficit---- over-- --- --- --<br>2~~~~~~~2<br>-I - - -- ---- - - ---------- ------------ ------ --- ----2 7- ---<br><!-- End of picture text -->
Table 5: Summary of counterfactual scenarios for combined investments

|Scenario|Country|Road infrastructure|Electrifcation|
|---|---|---|---|
|||Baseline||
|1|Djibouti, Ethiopia,<br>Kenya,Somalia|Speed and road conditions from latest<br>surveys|Limited access to<br>electricity|
||With r|oad infrastructure investments only||
|2|Djibouti, Ethiopia,<br>Kenya,Somalia|Higher speed along Corridors 1–4|Limited access to<br>electricity|
|||With electrifcation only||
|3|Djibouti, Ethiopia,<br>Kenya,Somalia|Speed and road conditions from latest<br>surveys|Electrifcation for<br>all|
|||With both investments||
|4|Djibouti, Ethiopia,<br>Kenya, Somalia|Higher speed along Corridors 1–4|Electrifcation for<br>all|

# **5.3.3 Employment Impacts**

While new roads reduce the share of employment in the agricultural sector for all countries, the impact varies across countries when reduction in border delays are also considered. Table 6 shows the changes in the shares of employment in nonagricultural sectors, which include manufacturing and services. The proposed investments in transport corridors would lead to a 1.5 percentage-point increase in the share of employment in nonagricultural sectors overall. Kenya would experience the largest increase, followed by Ethiopia, Djibouti, and Somalia. Trade facilitation measures that reduce border times by half would add little to the change in the share of employment in nonagricultural sectors in the Horn of Africa as a whole, but it would lead to large increases in the share of employment in nonagricultural sectors in Kenya and Djibouti and a decrease in Ethiopia. Lower transport and trade costs lead to more workers in the agricultural sector in Ethiopia, for which the country has a comparative advantage compared to its neighbors.

The impact of electrification on structural change is rather small. The electrification would lead to a 0.3 percentage-point increase in the share of employment in nonagricultural sectors overall, with the largest increase in Kenya and a decrease in Ethiopia.

The impacts from combined investments on structural change significantly differ from the sum of isolated investments and depend on the comparative advantage of each location in the Horn of Africa and the general equilibrium effects included in the model. An increase in productivity in manufacturing and service sectors can lead to an increase in employment in these sectors if the increased market access leads to an increase in demand for manufacturing and services; otherwise there can be a reduction in employment in these sectors. The largest reduction in the agricultural employment share happens when roads and trade facilitation are combined for Kenya, and when roads end electrification are combined for Djibouti and Somalia.

22
1990 to 43 in 2006. The share of Northern imports from the South covered by an EIA reached 19.5% in 2006. Furthermore, an increasing number of EIAs include TBT provisions involving the harmonization of technical regulations (21 North-South EIAs in 2006). A few EIAs promote the use of regional standards only (six in 2006), and the trade coverage of these EIAs is approximately 3.8%. Finally, one may note that the trade coverage of EIAs promoting the use of international standards (alone or in addition to regional standards) decreased between 1999 and 2006.

**Table 1. North-South EIAs and Trade**<sup>#</sup> **Coverage**

|||1990|1|999||2006|
|---|---|---|---|---|---|---|
||Nb|Trade<br>coverage<br>(%)|Nb|Trade<br>coverage<br>(%)|Nb|Trade<br>coverage<br>(%)|
|EIAs|4|0.4|12|15.8|43|19.5|
|EIAs with harmonization of technical regulations|0|0|5|14.2|21|15.7|
|Promotion of the use of regional standards only|0|0|2|2.1|6|3.8|
|Promotion of the use of international standards|0|0|2|12.1|12|11.8|
|(alone or in addition to regional ones)|||||||

_Source:_ Authors’ analysis based on data sources discussed in the text.<sup>#</sup> _Note_ : : Northern imports from the South.

# **5. The results**

As emphasized above, standards harmonization in North-South EIAs is expected to have distinct effects on South-South vs. North-South trade.

# **5.1 South-South trade**

This section analyzes the influence of standards harmonization in North-South EIAs on bilateral trade between Southern countries and disentangles trade-diversion effects from trade-deflection ones.

21
_HOTTER PLANET, HOTTER FACTORIES_ _11_ ious climate variables at high resolution and global scale. The data have global coverage that is gridded to a regular latitude-longitude grid of 0 _._ 25<sup>0</sup> _×_ 0 _._ 25<sup>0</sup> or _≈_ 27 _._ 5 _×_ 27 _._ 5km grid spacing, covering 1980 to the present. We use the ERA5Land data set of monthly temperatures and relative humidity measured within a range of 289 centimeters of soil depth to 2 meters above the surface level.

Using these sets of climate data, we perform two computations. First, we compute the WBT<sup>11</sup> in degrees Celsius to account for the effects of humidity on the human body when combined with high temperatures. It is a common practice in the literature to use WBT rather than dry-bulb or air temperature since the effect of changes in temperature varies at different levels of humidity (Kjellstrom et al., 2009c,a; Lemke and Kjellstrom, 2012; Adhvaryu et al., 2020; LoPalo, 2023). WBT provides a better measure for assessing the risks to the human body and health of both temperature and humidity, compared with using only air temperature. WBT is a nonlinear function of temperature and relative humidity, and it is often lower than (dry-bulb) temperature measures. We follow Chen and Chen (2022) and use the following formula to calculate the WBT: where _WBT_ is the wet-bulb temperature (degree Celsius), _T_ is the near-surface dry-bulb temperature (degree Celsius), and _rh_ is relative humidity (percent).

Second, for each geographic area _j_ within a radius of 30km around the establishment, we calculate the WBT deviations from the long-term average for each month of the year as follows: where ∆ _WBTj,t_ denotes the average deviation in WBT in location _<u>j</u>_ and year _t_ , _WBTj,mt_ is WBT in location _j_ for the month of _m_ , and year _t_ , _WBTj,m_ is the long-term average (typical) WBT for the month of _m_ in location _j_ .

A key contribution of this study is the estimation of the potentially non-linear effects of climate change on firm-level productivity. To achieve this, we group firms into four quartiles of WBTs: quartile 1: _≤_ 23 _._ 7<sup>0</sup> _C_ (the minimum WBT in

> 11All temperature measures are in degrees Celsius unless otherwise specified.
The internationalization or liberalization of financial markets matters for financial development as well as for productivity growth. First, the main direct positive effect of foreign banks on the level of financial development is to improve the access to financial services and lower the cost of borrowing, and at same time, it will also improve the quality of banking services. Second, foreign bank entry also has the indirect effect of increasing the competitiveness and efficiency of the domestic banking sector, and providing incentives to improve accounting, auditing, and rating institutions, as well as encouraging learning by doing by local banks (Aghion and Howitt 1992). Through entry and exit, new banks bring new knowledge, more varieties /products and innovative processes to the market and force-out some inefficient domestic banks. Productivity improves through resources reallocation from inefficient banks to more efficient ones.<sup>3</sup> Consumers and firms in nonfinancial sectors benefit from more efficient banking services and better products.<sup>4</sup> Empirical studies investigating the direct link between foreign banks and growth could not find any robust results. For example, Demirguc-Kunt, Levine, and Min (1998) cannot find any direct link between foreign banks and long-run economic growth after controlling for other factors associated with growth. Given the lack of empirical evidence on a direct link between banking sector openness and economic growth, researchers have

> 3 Schumpeterian creative destruction (Schumpeter, 1942) may explain the effects of entry and exit of firms and higher competition on productivity, in turn, on growth. For example, Aghion and Howitt (1992) produce an endogenous growth model in which vertical innovations, developed by a competitive research sector, are the source of economic growth. One implication of their model for service trade liberalization is that the entry and exit of firms and competition are good for improving productivity since the process encourages innovation and reallocation of resources from inefficient ones to efficient ones.

> 4 Besides these positive effects, there might be some costs associated with foreign bank entry: some argue that they may dominate the entire domestic financial market, and others consider that they may foster capital flight. But these arguments are relatively weak considering the new generations of trade and growth models and recent evidence associated with them.

3