rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> Figure 6: Quasi-non-anonymous growth incidence curve<br>Growth rate (%) on y-axis, population-weighted<br>10 1988-2008 ° 1993-2008<br>754% , annual growth annual growth<br>a a 10 SoG<br>2.5 seo}% Laon e 9°sso< aeeog % % ° aA3 °%o% £9 edgepres ernars pase 75 ¥ 2 °ee . . ee3 <e° eg Fv oo coe°°oe° e 6,<br>254¢; WS soete° weee F%8 F° eee5° eaeROARvon “ AROi2 Rese “ ra6 DOE ost oeA ee50 t¢af aahoe ae * aOe > a eeeeeo a.So, spot0Ee& %; res“ee $ Be eteree wes fk» ee© o %Fe,<br>=r ° ° ° eer eo 25 Bo oe : geo ocr oo : sf > oor ®<br>5 eo 5 ° *. ° eo ° ¢@ ° ° ° ° ° ®<br>7.5 7.5 °<br>-10<br>-10 °<br>0 2 4 6 8 1 0 2 4 6 8 1<br>90 1988-2008 80 1993-2008<br>80 zoomed-in zoomed-in<br>cumulative growth 7° cumulative growth<br>70 60<br>60 50<br>50 40<br>40 a ay i — ee Yh GL<br>30<br>30<br>20 20<br>0 2 4 6 8 1 0 2 4 6 8 1<br>Normalised rank in the 1988 global income distribution Normalised rank in the 1993 global income distribution<br>Solid line shows predicted value from kernel-weighted local polynomial regression Solid line shows predicted value from kernel-weighted local polynomial regression<br>(bw=0.05, epanechnikov, cube polynomial). The horizontal line shows growth rate (bw=0.05, epanechnikov, cube polynomial). The horizontal line shows growth rate<br>in mean of 40.77% (1.72% p.a.). Only countries observed in 1988 & 2008 (N=63) included. in mean of 33.53% (1.95% p.a.). Only countries observed in 1993 & 2008 (N=90) included.<br><!-- End of picture text -->
Policy Research Working Paper 6783

# **Abstract**

This paper provides new evidence on the factors affecting protracted credit contraction in the wake of the global financial crisis. The paper applies panel vector autoregressions to a global panel that consists of quarterly data for 41 countries for the period 2000–2011 and documents that domestic private credit growth is highly sensitive to cross-border funding shocks around the world. This relationship is significantly stronger in Central and Eastern Europe, a region with considerably stronger foreign presence, higher cross-border funding, and elevated loan-to-deposit ratios compared with the rest of the world. The paper shows that high foreign ownership per se does not appear to explain credit response differences to foreign funding shocks. Rather, there is a stronger response in countries that exhibit high loan-to-deposit ratios and a high reliance on foreign funding relative to local deposits. The results suggest that funding model differences were at the heart of the postcrisis credit contraction in several Central and Eastern European countries. These findings have important regulatory and supervisory implications for emerging countries in Central and Eastern Europe as well as for other countries.

This paper is a product of the Finance and Private Sector Department, Europe and Central Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at efeijen@worldbank.org.

_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 views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Appendix B: Additional results**

Table B.1: Overview of High-frequency <u>phone surveys used</u>

|Country|Region|Question<br>type|
|---|---|---|
|Burkina Faso|Sub-Saharan Africa|Consumption|
|Bulgaria|Europe & Central Asia|Income|
|Central African Rep.|Sub-Saharan Africa|Consumption|
|Congo, Dem. Rep.|Sub-Saharan Africa|Consumption|
|Gabon|Sub-Saharan Africa|Income|
|Ghana|Sub-Saharan Africa|Income|
|Guinea|Sub-Saharan Africa|Income|
|Gambia, The|Sub-Saharan Africa|Income|
|Guatemala|Latin America & Caribbean|Income|
|Honduras|Latin America & Caribbean|Income|
|Croatia|Europe & Central Asia|Income|
|Kazakhstan|Europe & Central Asia|Income|
|Kenya|Sub-Saharan Africa|Consumption|
|Lao PDR|East Asia & Pacific|Income|
|Mali|Sub-Saharan Africa|Consumption|
|Myanmar|East Asia & Pacific|Consumption|
|Mongolia|East Asia & Pacific|Consumption|
|Mozambique|Sub-Saharan Africa|Income|
|Mauritius|Sub-Saharan Africa|Income|
|Malawi|Sub-Saharan Africa|Income|
|Niger|Sub-Saharan Africa|Consumption|
|Nigeria|Sub-Saharan Africa|Income|
|Philippines|East Asia & Pacific|Income|
|Poland|Europe & Central Asia|Income|
|West Bank and Gaza|Middle East & North Africa|Income|
|Romania|Europe & Central Asia|Income|
|Sudan|Sub-Saharan Africa|Consumption|
|Senegal|Sub-Saharan Africa|Income|
|Solomon Islands|East Asia & Pacific|Consumption|
|El Salvador|Latin America & Caribbean|<br>Income|
|South Sudan|Sub-Saharan Africa|Consumption|
|Tajikistan|Europe & Central Asia|<br>Income|
|<br>Tunisia|<br>Middle East & North Africa|Income|
|Uganda|Sub-Saharan Africa|Consumption|
|Uzbekistan|Europe & Central Asia|Income|
|Zambia|Sub-Saharan Africa|Income|
|Zimbabwe|Sub-Saharan Africa|Consumption|

_Note_ : _Question type_ reports either income (preferred) or consumption variable from the phone survey used to calculate the change probabilities reported in Table B.2. The income change question asks whether the household experience a loss, gain, or no change in income since the beginning of the pandemic. The consumption loss question reports whether a household experienced a loss in consumption.

44
- 43 -

falling informal sector wages is fully consistent with the predictions of standard models in the literature such as that of Mincer (1976).

- 11 Official government estimates claim that unemployment rates among young people are of the order of 60Z or above. These estimates appear, however, to be derived residually by subtracting urban modern sector employment from estimated urban labor force.

- 12 Here we assume that the difference in the rate of technical progress between the agricultural sector and the rest of the economy is constant across different periods.

- 13 There are various aspects under the general concept of labor standards, thus covering regulations on children's work, right to periodic rest periods, work safety, etc. We will concentrate ourselves in the aspects more relevant to consider the labor market response to macro adjustment.

- 14 Naturally, all these labor-protective instruments cover the urban formal sector of the labor market. As often argued, they usually deal with a relatively small proportion of the total employment and create certain inequitable results in the context of macroeconomic policies.

- 15 One exception to this respect is Nigeria.

- 16 Labor demand functions have also been estimated using time series data in other LDC's. These usually indicate substantially less than perfect employment adjustment. For other examples from the overview series, see Lucas (1985) and Riveros (1988d).

- 17 A detailed analysis of government wage and employment behavior under a fixed budget constraint is given in Lindauer (1985).

- 18 Here we refer to an (internal) Pareto optimum between employers and unions such as, for example, at a Nash bargaining solution. The imposition of greater JSR must therefore lower employer utility (profit) if the level of union utility is at least maintained.
||Italy, the<br>Netherlands,<br>Spain, and<br>United<br>Kingdom||||of welfare, even when<br>usage demand is held fixed|
|---|---|---|---|---|---|
|Austin & Dinan<br>(2005)|United States|2001|Prices, unit sales, and fuel-<br>economy ratings for<br>vehicles sold|Simulation model|A gasoline tax would<br>produce greater immediate<br>savings by encouraging<br>people to drive less, and<br>eventually to choose more-<br>fuel-efficient vehicles|
|Jacobsen<br>(2013)|United States|1997-2001|Household demand data<br>from National Household<br>Travel Survey and supply<br>data, vehicle characteristics|Simulation model|Dynamic impacts in the<br>used car market comprise<br>nearly half the gross<br>welfare cost of corporate<br>average fuel economy and<br>fall disproportionately on<br>low-income households|
|Anderson &<br>Sallee (2016)|United States|NA|NA|Theoretical Model|Standards are substantially<br>less efficient than a fuel<br>tax|
|Parry & Small<br>(2005)|United States<br>and United<br>Kingdom|NA|VA|Theoretical Model and<br>Empirical Estimations<br>based on parameter<br>values from the<br>literature|A direct tax on amount of<br>travel (vehicle-miles)<br>performs better|
|Ito & Sallee<br>(2018)|Japan|2001-2013|Characteristics of new<br>vehicles sold|Simulation|Attribute-based regulation<br>is an imperfect substitute<br>for flat policies with<br>compliance trading|
|Whitefoot &<br>Skerlos (2012)|United States|2006|Data on technology features<br>(e.g., cylinder deactivation)|Simulation|There is larger incentive to<br>produce light trucks than<br>to produce passenger cars,|

53
26 Yet another way to examine the characteristics of recent regional trade agreements is to note that one of the important motives of the so-called “New Regionalism”, particularly for smaller economies, is to design rules to attract more foreign direct investment and to strengthen institutions in order to participate in global and regional production sharing (Ethier 1998, Salazar-Xirinachs 2005). Thus one way to evaluate the performance of FTAs of East Asian and Latin American countries is to examine the competitiveness of East Asian and Latin American countries in items such as components and parts, using the revealed comparative advantage (RCA) index. The index is defined as: where _j_ indicates the product value and _k_ home country. Xjk and Xwk represent the product value of _j_ exported by country _k_ and the world; Xk and Xw are total exports of _j_ by country _k_ and the world. If the index has a value greater than one, country _k_ has a comparative advantage in the production of product _j_ . If the index has a value smaller than one, the industry of the country has a comparative disadvantage.

Suppose we go further and differentiate the RCA index for exports from that for imports. When the RCA index is greater than 1 for exports of components and parts,<sup>8</sup> we can reasonably argue that the economy has a comparative advantage in “processing”. When the RCA index is greater than 1 for imports, we say that the economy has comparative advantage in “assembly”. The RCA indices for East Asian and Latin American imports and exports of parts and components for various years are shown in Table 7 and Table 8.

> 8 The list of products that are classified as components and parts is available upon request. The list is compiled from the UN COMTRADE statistics by the authors.
**Table 9:  Income Inequality has Risen Sharply in Palanpur**

||Theil L Measure|Gini Coefficient|
|---|---|---|
|1957/8|0.188|0.336|
|1962/3|0.282|0.390|
|1974/5|0.169|0.253|
|1983/4|0.174|0.307|
|2008/9|0.336|0.427|

Analyses of inequality in rural India commonly focus on social stratification – particularly differences between castes – as an important source of income inequality. Castebased inequality is considered notoriously durable and has been the subject of a lot of work across the social sciences (e.g. Dumont 1966, Deshpande 2000). In light of the evidence presented above pointing to a noticeable increase in social mobility amongst Jatab households since 1983, one might expect that that a decomposition of inequality in Palanpur by caste, would reveal that between-caste differences have come to account for a significantly lower share of overall inequality in 2008/9, relative to earlier years.<sup>8</sup> Some support is given to this contention in Table 10 where it can be seen that the contribution to total inequality of between-caste differences is 17% in 2009/9, down from 29% in 1983/4. More surprising however, is that from this decomposition analysis differences between castes have never appeared to be particularly significant in Palanpur: even in 1983/4 more than 70% of income inequality can be attributed to within-caste differences between individuals. This is unexpected in light of the strongly castebased narrative offered above to explain both the organization of economic activity in Palanpur and the evolution of living standards over time across different groups in the village.

**Table 10:  The Contribution To Inequality of Caste Differences Has Changed Little**

||Theil L Measure|Within-Caste<br>Contribution|Between-Caste<br>Contribution|
|---|---|---|---|
|1957/8|0.188|77%|23%|
|1962/3|0.282|82%|18%|
|1974/5|0.169|69%|31%|
|1983/4|0.174|71%|29%|

8 Following Bourguignon (1979), Cowell (1980) and Shorrocks (1980) inequality by population sub-groups is a basic tool of inequality analysis, permitting the quantification of the “contribution” to overall inequality of differences in average incomes across a given set of population sub-groups.

21
−0.26±0.56 % when compared with the corresponding TCCON data. Per the ESA’s recommendation, we use only pixels with quality values greater than 0.5. The data have been downloaded from the ESA’s AWS repository managed by MEEO (Meteorological Environmental Earth Observation).<sup>14,15</sup> We filter the bias-corrected XCH4 data for local concentration anomalies, or differences between observed and background CH4 at each point.<sup>16</sup> We calculate background CH4 using the methodology of Hakkarainen et al. (2019), which isolates local anomalies from the three background components described above. We compute the daily median XCH4 for each 10degree latitude band and linearly interpolate the result to each S5P observation with 1-degree resolution. Following Hakkarainen, we use the median as the representative value because it is not skewed by extreme observations. We subtract this background value to compute the local anomaly for each observation. Then we compute monthly mean values of concentration anomalies for each 5-km grid cell in our database.

For this exercise, we overlay the 5-km grid with the sampling polygons for our high-priority GGUs. Numerous technical and atmospheric factors produce highly-varied sample counts. To ensure robust estimates, we confine our exercise to GGUs with at least 20 observations in each year.

Table 6 provides summary statistics on sample counts for the 775 GGUs that meet this condition. The median GGU has 2,033 S5P observations for the period 2019 – 2022, while the leastrepresented GGU has 92 observations and the most-represented has 77,011.

**Table 6:  Statistics for GGUs with minimum yearly S5P sample of 20**

GGU S5P Observations, 2019 - 2022 GGUs Min P10 P25 P50 P75 P90 Max 775 92 464 980 2,033 3,861 8,123 77,011

# **5.  Priority Area Monitoring – Illustrations**

This exercise aims to use methane data from the Sentinel-5P platform to track changes in emissions-intensive areas identified by EDGAR. In the previous section, we developed a methodology for sampling S5P data for those areas. We illustrate our approach for three areas dominated by important CH4 sources: Madrid Province, Spain [two large landfills]; Karnal District, Haryana State, India [irrigated rice production]; and Al Amarah District, Maysan Governorate,

> 14 https://www.meeo.it/

> 15 - The data are available in NetCDF format at the ESA’s AWS repository, https://meeo <u>s5p.s3.amazonaws.com/OFFL/L2__CH4, with filenames catalogued at</u> https://scihub.copernicus.eu/catalogueview/S5P/

> 16 For further discussion, see Dasgupta, Lall and Wheeler (2022, 2023).
# **Table 4: Effects of Household Income on the Propensity to Pay Different Types of Bribes IV Estimates (2SLS)**

||**Pro**<br>|**pensity top**<br>|**ay**<br>||||
|---|---|---|---|---|---|---|
||**Admi**|**ssion**|**Admiss**<br>**Oth**|**ion and**<br>**ers**|**Payments**<br>**Rece**|**Without**<br>**ipt**|
||(1)|(2)|(3)|(4)|(3)||
|**Per Capita Income**|**-0.145**<br>**(-2.62)*****|**-0.146**<br>**(-2.50)*****|**-0.140**<br>**(-2.47)** **|**-0.157**<br> **(-2.75)*****|**-0.090**<br>**(1.46)**|**-0.108**<br>**(-1.82)***|
|Individual and Household Controls|Yes|Yes|Yes|Yes|Yes|Yes|
|Regional Fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|
|**Sign and Significance of the Instru**|**ment in Firs**|**t stage**|||||
|Heavy Rainfall Dummy|-0.642||-0.642||-0.642||
||(3.12)***||(3.12)***||(3.12)***||
|Interactions Based Instrument||2.26||2.26||2.26|
|||(3.28)***||(3.28)***||(3.28)***|
|Angrist-Pischke F Statistic|9.72|10.78|9.72|10.78|9.72|10.78|

Notes: (1) Standard errors are clustered at primary sampling unit (PSU) level (2) Robust z statistics in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1% (3) Individual and household controls Used in the Odd Numbered Columns are: Age, Gender, and Religion of Household Head, and Household Size and Number of schools age children. Even Numbered Columns also Include Household Head's Age Squared and Cubed as additional Regressors.

(4) The instrument in Even Numbered Columns is the Predicted Income from the "zero stage" using interaction of Heavy Rainfall Dummy with Household Head's Age and Religion.
without taxing the cognitively heavy systems of attention and memory.

# **2.2 Game Design**

In this study we play a simple dice game with participants to provide an experience-based learning forum to convey low probabilities of gambling. Gambling prevalence is often explained by the fact that individuals do not understand how low probabilities translate into the frequency of winning as probabilities such as 14 million to one are unlikely to lie within the range of everyday experiences (Smith and Walker 1993). Hence, our game was meant to provide an intuitive mapping of probabilities through active experimentation.

The game used regular six-sided dice as props and was administered in the field at the conclusion of a baseline survey on financial access. The game was administered by our trained staff and at the individual respondent level (see Appendix A for the exact protocol used). We first let participants roll one die until they obtained a six. Then we added another die and let them roll until they simultaneously obtained two sixes, which took them much longer. The participants were then told the equivalence of number of dice and the odds of winning different prizes in the lottery. The chance of having four right numbers in the lottery, for example, was equivalent to rolling all sixes with five dice and the odds of winning the jackpot was smaller than getting all sixes with nine dice.

The study sample consisted of 840 poor households in the Eastern Cape and KwaZulu-Natal province of South Africa. Half the study sample was randomly assigned to receive the debias treatment while the other half received a more traditional financial education module on avoiding expensive credit. (For the expensive credit treatment protocol see Appendix B.) Both the debiasing and credit modules took an average of 10 minutes and did not have any overlapping content. Second, the number of rolls it took for participants in the treatment group to get two sixes provided additional variation in the intensity of treatment. Moreover, the longer it took to roll two sixes, the clearer it became to the participants that their chance of winning was low.

8
# FIGURE 4

<!-- Start of picture text --> TOTAL EXPENDITURES AND REUENUES OF THE CPS (AS V. OF UP)<br>60<br>55 . A<br>45 ..<br>40 . \ . . s- . . . . \<br>3S / ' . . . ., . . , .-. . . . .<br>30 ..... ... . . .. . :.--<br>25<br>1960 1965 1970 1975 1989 1985<br>_ TEGDP ....... TRGDP<br><!-- End of picture text --> Figure 4 shows'the evolution of total expenditures and revenues (as percentage of GDP) of the Consolidated Non-Financial Public Sector (CPS). The first thing to notice is that Revenues have historically shown a growing trend similar to that of Expenditures while beir.g systematically below them. Total Revenues rose from a low level of about 23% in 1962/65 to a high of 41% in 1985. It should be mentioned that the Revenue measure does not incorporate the Current Revenues from Public Enterprises. This high growth in fiscal revenues in the face of a stagnant economy should be enough to invalidate the commonly held claim that the basic problem in Argentina is that the public does not pay taxes. The fe:t of the matter is that not only is fiscal pressure very high bu.t it has grown at a much faster rate than that of GDP in the last 25 years.

It is the case that even though fiscal pressure has been high, fiscal spending has also grown and has systematically exceeded revenues. Expenditures of the CPS got to a level of 55% of GDP in 1983 (up from a level of 30% in the decadesof the 1960s) before a serious attempt was started to reduce government spending. Since then government spending was reduced by 11% of GDP but this reduction was wiped out by the increased quasifiscal spending done by the Central Bank in order to service the accumulated level of financial liabilities of the institution.

10
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