rafmacalaba/datause-encoder-data huggingface dataset:
4 third section nresents the main findings of the second report on adjustment lending on effectiveness of adjustment lending and on implementation of programs. Section 4 reviews the findings of RAL-2 on policies for the recovery of growth. Finally, Section 5 presents some lessons on program design for Eastern Europe.

# II. EMERGING CONSENSUS ON 'ROGRAM DESIGN

From research done analyzing economic reforms in developing countries, both successful and some unsuccessful, some important lessons have emerged. these lessons have served as the basis for an emerging professional consensus on program design. Of course, the particulars of a country-specific adjustment programs need to take into account the economic and political conditions in each country.

For reforms to be succesiful, they should have a good chance of making important progress in removing the impediments which prevent obtaining the maximimum output from existing resources. In countrien with major impediments to resource reallocation in the form of high and variable inflat..ion, high level and high variance of tariff rates, rentrictions to factor mobility, illdefined property rights, and a large public sector sheltered from efficiency considerations, any reform effort that does not address these barriers would have a low chance of success. Furthermore, without removing these impediments, reforms will have low credibility and could unleash responses that could result in a deterioration of the economic situation instead of an improvement (Calvo, 1989).

In countries that are experiencing acute macroeconomic imbalances manifested in the form of high open or repressed inflation, large fiscal
more banks are slated for privatization, but with no definite date set. The privatization and liquidation of state banks under PROES has contributed significantly to the decrease in government ownership in the Brazilian banking system. By end-1999 it has fallen to 43% of total assets. This decline has been accompanied by a significant increase in foreign participation in the Brazilian banking system (Table 1).

# **3. PROES and the determinants of the different options**

While there is a large literature analyzing the politics of privatization of non-financial companies, there are few papers discussing the political decision process to privatize government-owned banks.<sup>24</sup> We therefore build on the economics of state ownership of banks for our hypothesis testing on states’ different choices under PROES.<sup>25</sup> To explore the factors behind the different methods of transformation of state banks, we construct a variable capturing the different options. _Transformation_ equals one if the state bank was liquidated, two if the federal government took it over, three if the state government privatized it, and four if the bank was restructured and stayed in government ownership. This variable is structured in a way that higher values signify more decision power retained by the state government.<sup>26</sup> However, the decision power of state government varied, since five state banks were already taken over by the Central Bank under the RAET before the PROES was

> 24 On the politics of privatization in general, see Perotti (1995) and Biais and Perotti (2002). Boehmer et al. (2005) use a panel of 101 countries over the period 1982-2000 to analyze the determinants of bank privatization decisions, while Clarke and Cull (2002) assess the factors behind the timing of provincial bank privatization in Argentina.

> 25 Compare La Porta et al. (2002).

> 26 We also tried a simple dummy variable that takes value one if a bank is restructured and zero otherwise.  The use of dummy variables as dependent and as independent variables (see below), however, posed econometric problems.

11
The data used in this paper are from the 2005 Living Standards Measurement Study survey (ALSMS05), carried out by the Albania Institute of Statistics (INSTAT) in collaboration with the World Bank, on a sample of 3,640 households. The ALSMS05 includes a typical household questionnaire covering general household demographics, education levels, asset ownership, expenditures and labor market participation. In addition, the survey also provides community-level data, which include information on access to services and infrastructure in the locality, as well as price information. The ALSMS05, though, differs from a typical LSMS in at least two ways. First, the household questionnaire includes an unusually detailed module on migration, both internal and international, of both current and former household members. Second, the questionnaire administered in the spring contained a short module for the proper identification of farm households within the nationally representative sample. A detailed farm survey was fielded the following fall on a sample of 1,849 farm households, as identified in the spring visit. These farm households form the basis for the analysis in this paper.

Table 1 presents descriptive statistics of the variables used for the analysis, by migration status. A household is classified as a migrant household if, at the time of the survey, it had a former household member (mostly adult children of the household head) currently living abroad. Based on this definition, 33.4 percent of the sample has at least one international migrant. Of these, 50.4 percent has more than one former household member abroad.

Significant differences are found in the average number of hours worked in agriculture by households in the two groups, as well as in the amount of labor effort in agriculture by the males in the household. Despite owning more land on average, households who have individuals currently migrating abroad devote less hours to agricultural labor, mostly driven by considerably lower work effort by male members of the household. No significant differences are found across groups in the number of hours worked by female household members, either in total or per capita terms.

Similarly, no significant difference across groups is detected in the farm’s technical efficiency and level of total household agricultural income. However, households with migrants exhibit significantly higher total incomes. Although no 7
<!-- Start of picture text --> Policy, Ftesearch, and External Affairs<br>Agricultural Pollcles<br>WPS 650<br><!-- End of picture text -->

- This paper a product of the Agricultural Policies Division, Agricultural and Rural Development - Department is part of a larger effort in PRE to analyze the agricultural transition in former centrallyplanned economies. Copies are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Cicely Spooner, room N8-039, extension 30464 (26 pages, with tables).

New land tenure arrangements in the USSR require that agricultural producers pay for land use. The current distorted pricing system and the absence of functioning land markets complicate land valuation, and slow the adontion of new property relations.

In a market economy that functions well, agricultural land would earn its approximate marginal value product in agricultural production. This value can be measured empirically from production data and can serve as an appropriate initial value for users' fees.

Brooks estimates marginal value products for land for 1,032 collective and state fanns in Lithuania using farm-level data for 1986 and 1987 and compares the marginal value producLs derived from actual received producer prices with those derived from border prices with altemative assumed exchange rates for the ruble.

The PRE Working Paper Series disseminates the findings of work under way in the Bank's Policy, Research, and External AffairsComplex. An objective of the series isto get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy.

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zero only if reserves increase by 2.0 standard deviations or more relative to the mean. If global reserves increase by two standard deviations relative to the mean, a 10 percent increase in battle-related deaths is associated with a reduction of greenfield FDI in the oil-and-gas sector of approximately 4%, ceteris paribus. Hence, our results thus suggest that during the estimation period, the geographic-constraints mechanism was at work.

**Table 7 Effect of Political Conflict on Greenfield FDI in the Oil and Gas sector**

||LSDVC esti<br>|mations, green<br>|field FDI in U<br>|SD millions<br>|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|BRDt-1(ln)|0.064|0.090|-0.091|-0.097|
||(0.077)|(0.078)|(0.114)|(0.130)|
|Ln(BRD)*gasoilreservest- 1||-0.090*|-0.156**|-0.156**|
|||(0.046)|(0.055)|(0.055)|
|Ln(BRD)*gasoilindext-1|||0.002*|0.002*|
||||(0.001)|(0.001)|
|Ln(BRD)*localizedt-1||||0.013<br>(0.141)|
|Major Gas/Oil discoveriest-1|-0.391|-0.332|-0.337|-0.336|
||(0.507)|(0.507)|(0.505)|(0.505)|
|FDIt-1(ln)|0.086*|0.086*|0.081+|0.081+|
||(0.043)|(0.043)|(0.043)|(0.043)|
|GDPt-1(ln)|-0.962|-0.950|-1.004|-1.008|
||(0.877)|(0.877)|(0.874)|(0.877)|
|Population (ln)|13.495**|14.050**|13.965**|13.973**|
||(4.312)|(4.330)|(4.313)|(4.322)|
|WGI regulatory qualityt-1|1.287|1.121|1.104|1.096|
||(0.997)|(1.002)|(0.998)|(0.996)|
|WGI Corruptiont-1|-0.419|-0.482|-0.656|-0.659|
||(0.905)|(0.905)|(0.907)|(0.909)|
|Polity Indext-1|-0.061|-0.038|-0.052|-0.053|
||(0.073)|(0.074)|(0.074)|(0.074)|
|Real Exchange Ratet-1(ln)|0.415|0.470|0.468|0.466|
||(0.545)|(0.544)|(0.542)|(0.543)|
|Exchange Rate Volatilityt-1|-2.525|-1.560|-3.752|-3.798|
||(11.240)|(11.242)|(11.206)|(11.208)|
|Inflationt-1|0.009|0.010|0.010|0.010|
||(0.012)|(0.012)|(0.012)|(0.012)|
|Observations|707|707|707|707|
|Number of countries|90|90|90|90|
|Country FE|Yes|Yes|Yes|Yes|
|Year FE|Yes|Yes|Yes|Yes|

The gas and oil reserves variable is standardized, and the gas and oil index is a price index. Bootstrapped standard errors are in parentheses. *** p<0.001, ** p<0.01, * p<0.05 The effect of political violence is positively moderated by oil and gas prices, indicating that the effect of battle-related deaths on FDI flows to the oil and gas sector depends positively upon the global prices of oil and gas. This dependency implies that during commodity booms when prices are high, MNEs are more likely to enter countries marred by political conflict than when prices are low. Figure 5b shows that only in cases of exceptionally high oil and gas prices do the effects of political violence 37
Table 3: An extract of the 20 4-digit strictly green occupations with the highest green task intensity <u>(GTI) and the total employment in each</u>

|||GTI-||
|---|---|---|---|
|ISCO|Occupational Title|Strict|n|
|9161|Garbage collectors|79.2|61023|
|2112|Meteorologists|77.8|463|
|2211|Biologists, botanists, zoologists and related professionals|75.0|3603|
|2114|Geologists and geophysicists|58.3|3048|
|2210|Scientist|50.0|1581|
|8163|Incinerator, water-treatment and related plant operators|50.0|22455|
|3222|Sanitarians|45.0|5058|
|9321|Assembling laborers|41.7|2803|
|3119|Physical and engineering science technicians not elsewhere classified|40.0|3112|
|2149|Architects, engineers and related professionals not elsewhere<br>classified|36.7|6971|
|2213|Agronomists and related professionals|33.3|6101|
|3213|Farming and forestry advisers|33.3|3831|
|5161|Fire-fighters|33.3|19234|
|7134|Insulation workers|33.3|275|
|2142|Civil engineers|28.6|15455|
|2113|Chemists|25.0|1109|
|7132|Floor layers and tile setters|25.0|34631|
||||20129|
|7231|Motor vehicle mechanics and fitters|22.9|2|
|3112|Civil engineering technicians|22.2|10641|
|6141|Forestryworkers and loggers|20.0|12121|

Notes: Own calculations using PALMSv3.3. Note: the 1-digit code for each occupation is simply the first digit in the 4-digit span. The 2-digit code is simply the first 2-digits in the 4-digit span.

Strictly green (4-digit) occupations are a mix of high-level, mid-level, and elementary jobs. The occupation with the highest green task intensity is the elementary occupation of garbage collectors (code 9161) with a GTI of 79.2 (Table 3). This means that 79 percent of tasks in this occupation’s description include terms from the strictly green list. The high GTI for garbage collectors is attributable to the terms “ _recycling”_ and “ _collecting recyclable materials or items”_ in the occupational tasks description, all derivations of the green dictionary term “ _recycl12”_ . This root term appears in most tasks for this occupation.<sup>26</sup> The next two greenest occupations require high skills. Meteorologists (code 2112) and biologists and related professionals (code 2211) have GTIs of 77.8 and 75.0 respectively; both are classified as high-level occupations.

The majority of strictly green occupations are high-level, though a disproportionate share of 26 Recall that the GTI score is calculated using ISCO-08 which is a newer version of occupation classification to ISCO-88. Our data PALMS is based on ISCO-88 and the occupation Garbage collectors, ISCO-88 code 9161 maps to two ISCO-08 occupations. Garbage recyclers and collectors (code 9611) where 3 out of 4 tasks in this occupation are green with a GTI score of 75 and Refuse sorters (code 9612) where 5 out 6 tasks are green with a GTI score of 83. The GTI score for ISCO-88 code 9161 (Garbage collectors) is then 79, the average of the two which is what we report in the paper.

12
|**Table 4: Impact of Trainin**|**g on Employment as Measured in So**<br>Ever formally employed between <br>course end and Jan 2012<br>(time of follow-upsurvey)|**cial Security Data**<br> Formally employed in<br>August 2013|<br>Formal Income<br>earned in August 2013|Ever formally employed between<br>course end and Nov 2013|Ever left a formal job<br>between course end<br>and Nov 2013|
|---|---|---|---|---|---|
|ITT Estimate|0.026**|-0.009|-4.427|-0.005|0.015|
||(0.012)|(0.012)|(19.935)|(0.011)|(0.012)|
|Control Mean|0.424|0.427|553.820|0.662|0.506|
|Control Std. Dev.|0.494|0.495|796.571|0.473|0.500|
|Number of Observations|5896|5896|5896|5896|5896|

Notes: Robust standard errors in parentheses. *, **, and *** indicate significance at the 10, 5 and 1 percent levels respectively. All regressions include controls for course*gender*age group lotteries applied for.

37
U.S. Interagency Working Group (USIAWG) on Social Cost of Carbon, United States Government. Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. May, 2013. Revised July 2015. Available at <u>https://www.whitehouse.gov/sites/default/files/omb/inforeg/scc-tsd-final-july-2015.pdf</u> Vermeulen, B., Goos, P. and Vandebroek, M., 2008.Models and optimal designs for conjoint choice experiments including a no-choice option. _International Journal of Research in Marketing_ 25, 94-103.

World Bank. (2009) _Forests Sourcebook: Practical Guidance for Sustaining Forests in International Cooperation_ . World Bank: Washington, D.C.

40
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Policy Research Working Paper 5210

# **Abstract**

World prices for staple foods increased between 2006 and 2008, and accelerated sharply in 2008. Initial analysis indicated that the adverse effects of higher food prices in Uganda were likely to be small because of the diversity of its staple foods, high level of food self-sufficiency, and weak links with world markets. This paper extends the previous analyses, disaggregating by regions and individual food items, using more recent price data, and estimating the impact on consumption poverty. The analysis finds that poor households in Uganda tend to be net buyers of food staples, and therefore suffer welfare losses when food prices increase. This is most pronounced in urban areas, but holds true for most rural households as well. The diversity of staple foods has not been an effective buffer because of price increases across a range of staple foods. The paper estimates that both the incidence and depth of poverty have increased—at least in the short run—as a result of higher food prices in 2008, increasing by 2.6 and 2.2 percentage points, respectively. The increase in poverty is highest in the Northern region, which is already the poorest in Uganda. The need for mitigating social protection measures appears to be greater than previously recognized. Not only are the negative impacts larger, but they are also much more widespread geographically. This suggests the need for continued close monitoring of the situation, including monitoring the adequacy of existing safety nets and feeding programs.

This paper—a product of the Poverty Reduction and Equity Group, Poverty Reduction and Economic Management Network—is part of a larger effort in the department to assess the poverty and distributional impacts of rising food prices and other changes in global and domestic food markets. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at ksimler@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
for supply chains trading more complex products.<sup>20</sup> Though the paper does not attempt to nail down the mechanism behind this somewhat unexpected finding, a plausible explanation is that firms that produce more complex products value supplier-specific relationships more and take great care to preserve them when faced with uncertainty and disruption.

The importance of relationship-specific investments in global supply chains, and international trade more generally, has been emphasized in the literature (see 2020 WDR for an overview). Seen through this lens, it is perhaps not surprising that the US firms that appear in the Panjiva data and trade internationally did not on average sever existing relationships during the pandemic. Furthermore, the additional demand for certain products, e.g., face masks or electric batteries, may have led them to seek new trading partners. At any rate, though supply side shortages due to lockdowns contributed to net separations, overall the extensive margin of trade resulting from the combination of supply and demand forces indicates--- contrary to popular claims---strong resilience during the pandemic, as shown in Figure 5.

This message is reenforced in a few other papers that explore the economic effects of the pandemic. Stumpner (2022) studies regional lockdowns in China and shows that with the exception of the Shanghai lockdown of April 2022, the other regional disruptions in China due to COVID had no effect on international trade. He concludes that regional lockdowns could <mark>still reduce aggregate trade, but only if they were exceptionally stringent and implemented in an economically important province such as Shanghai.</mark> Using data for 64 countries, Bonadio et al (2021) document a large contraction of economic activity (an average 29.6% drop of GDP) during the pandemic. But only a small fraction of this contraction (ca. 23%) can be attributed to foreign shocks that are intermediated through final and intermediate goods trade. Moreover, simulations based on a global network model indicate that global supply chains alleviated the pandemic-induced contraction: the downturn in the 64 countries of their sample would have been worse on average if there were no international trade and supply chains relied on domestic inputs only. The reason is that elimination of foreign inputs would have increased reliance on domestic inputs which were also affected by the pandemic.

> 20 They use a few alternative measures of complexity: The number of products a particular firm buys from suppliers; the share of total purchases accounted for by differentiated products; and the average number of inputs that are necessary to produce each firm’s product.

26
# **1. Introduction**

Social relationships often underlie access to and usage of financial services. Guiso et al. (2004) argue that financial contracts are the “ultimate trust-intensive contracts” and thus social relationships that build such trust are crucial for financial development. The accumulated level of trust within a society, often referred to as social capital, is linked to greater financial development (Guiso et al., 2004), higher rates of growth (Knack and Keefer, 1997; Knack and Zack, 2001), a more resilient financial system (Lin, Levine, and Xie, 2016), and the presence of large organizations (La Porta et al., 1997).<sup>2</sup> Social capital has typically been measured using proxies for trust, trustworthiness, or association intensity, but a key dimension of various types of social capital measures is their radius (Fukuyama, 2000). The scope of social capital within a group, and the implicit trust and trustworthiness within that group, have either a narrow or a wide radius. Those with a narrow radius, such as families, grant benefits to members of the group, but often to the exclusion of other members of the society. In contrast, social groups with a wide radius benefit a larger number of members of the society, and thus confer benefits more widely. Since different types of social groups have differing levels of trust and scope of influence, it is important to examine how those types of social capital differentially affect access to resources and welfare.

We contribute to the literature on social capital by examining how belonging to two social groups within China, the family and the ruling party, affects access to finance, and how that participation affects private welfare as measured by household consumption.<sup>3</sup> We emphasize at the outset that our measures of consumption are net of within-family transfers, so coefficients on financial variables are not picking up the

> 2 See Keefer and Knack (2005) for an excellent summary of this literature.

> 3 Our work is therefore related to that of Besley and Levenson (1996), who find evidence that participation in informal lending networks led to greater consumption of durable goods in Taiwan, China, from 1977 to 1991. Using historical loan contract data from low-income rural villages in China in the 1930s, Brandt and Hosios (2010) also show that informal loans were predominantly used for consumption purposes. They document that a large share of these loans carried no interest rate and argue that these arrangements should be interpreted as “long-term reciprocal insurance or patronage relationships between households.”

2