rafmacalaba/data-use-mentions-extended huggingface dataset:
The official Chinese national accounts do not contain any estimate for the capital stock for the whole economy. Yet such a figure is necessary in order to determine past performance of the economy and its likely future path. This is the more so in China where the level of investment is particularly high (Figure 1). Concerns have been raised that there has been over-investment so reducing rates of return and the growth of productivity. Changes in the structure of the capital stock over time can change the average rate of return and the productivity of capital, so obscuring the underlying changes in productivity. This is particularly the case in China where the national accounts measure of the rate of sectoral return is assumed to be zero for most of the housing, infrastructure and government sectors. Thus, the question of whether there has been over-investment requires evidence both on the overall capital stock and its distribution across different sectors of the economy.

**Figure 1 Investment rate**

<!-- Start of picture text --> Current prices, % GDP<br>50<br>45<br>40<br>35<br>30<br>25<br>20<br>1981 1986 1991 1996 2001 2006 2011 2016<br>Source: NBS and author estimates<br><!-- End of picture text --> There have been many attempts to estimate the total capital stock of the economy, given the absence of official estimates. They have all been faced with similar problems. Even though investment data are available since 1952 on an internationally agreed basis, there is uncertainty about the initial value of the capital stock at that date, following a long period when the economy had been impacted by war and revolution. Moreover, in contrast to the aggregate data, the most detailed figures on investment continued to be gathered under the principles set out in the early 1950s rather than using the internationally agreed System of National Accounts (SNA). In addition, the gathering of economic data
’, previous research suggests that rehabilitated roads rapidly deteriorate again, given a lack of maintenance (Bachmann and Schouten 2018; Schouten et al. 2022). Does the effect of road rehabilitation on violence wane as the road quality gradually decreases again?

We first assembled a new database of the main transport infrastructure projects that occurred in the DRC since the end of the Second Congo War in 2003. A comprehensive list of such projects did not exist. We collected project data (start and completion years, cost, location, and type of infrastructure) from multiple sources, including international donors and government agencies, to create a panel of geolocalized investments. Our final panel of large inter-city road investments includes 192 projects (see Appendix B).

To answer our first question, we estimated the causal impacts of road construction on conflicts. Establishing causal links is challenging because of the interaction of road projects and the activity of armed actors with other, often unobserved factors, such as conflict dynamics and economic activity. For instance, mining (a key economic activity in eastern DRC), outbreaks of violence, and road construction are all placed endogenously, often reacting to each other (cf. Luo et al. (2021)). We address this issue of causality between roads and conflicts in three ways. First, we show that road projects do not select into peaceful regions. This means that it is unlikely that armed violence generally forces road rehabilitation out of a conflict-affected region. Second, we use an identification strategy exploiting the fact that a road project crosses a 55km by 55km cell. Such localized treatment is unlikely to be related to local violence trends as the project completion is recorded at a higher level.

2
of provisions for 100 PTAs in force in 2011 signed by mostly developed countries that contribute to more than 90 percent of world trade. In an effort to include a larger number of developing countries, Hofmann et al. (2016) updated the WTO data set and coded all the remaining agreements notified to the WTO and in force until 2015.

The number of trade agreements and their content changed dramatically since the early 1990s (Figure 1). The number of PTAs in force increased slowly in the 1960s and 1970s and then remained constant until the beginning of the 1990s when a large number of agreements entered into force. The number of PTAs has increased more than fivefold from 51 agreements in 1990 to 279 in 2015. Along with the number, the content of trade agreements has changed. The number of provisions included in PTAs raised over time suggesting an increase in the “depth” of agreements. The majority of PTAs signed after 2003 include at least 10 legally enforceable provisions. That is, modern PTAs are “deep” in the sense that they cover substantially more policy areas than traditional (or “shallow”) PTAs that focused mostly on tariff liberalization.

4
to MNREGA are clearly not satisfied and so our predicted changes in production should not be interpreted as predictions of the actual change in production after the implementation of MNREGA. Rather, they are estimates of one component of the change in farmer incomes and profits due to MNREGA. In practice the other impacts of MNREGA on farmer income and profits could have added to or subtracted from these estimated changes.

25 We use the average of rice and wheat across all of India, taken over the years from 2009 to 2013, following MNREGA implementation. Data available here: `https://agmarknet.ceda.ashoka.edu.in/` 14
# **Figure 10. Kernel distribution estimates of consumption per-capita**

<!-- Start of picture text --> Poverty line Vulnerability threshold<br>0 500 1000 1500 2000 2500<br>Household consumption per-capita<br>2005 2012<br>.002<br>.0015<br>.001<br>Kernel density<br>.0005<br>0<br><!-- End of picture text --> Bandwidth: 2 Source: IHDS, 2005 and 2012 Our decomposition exercise can help construct counterfactual scenarios that are useful to demonstrate vulnerability to specific events, like economic and policy shocks. The coefficients in Table A4 in the Appendix show the potential “loss” in poverty reduction if each factor had remained at its 2005 level, for each household. For example, a (hypothetical) economic shock that drove remittances down to its 2005 levels would have led to around 3 percent higher rural poverty and 1 percent higher urban poverty compared to what is observed now. Similarly, if benefits from government programs had been unchanged from the 2005 levels, rural and urban poverty in 2012 would have been higher by 1 and 0.5 percentage points, respectively.

# **5. Conclusion**

There has been much speculation and debate around the causes and drivers of the rapid poverty reduction in India seen from official data over the last decade. Our paper is an attempt to contribute to this debate, using evidence from two rounds of IHDS panel data that cover the period 2005 to 2012, which show trends roughly comparable with those from the official data sources for similar years. This paper attempts to understand the broad directions of changes from a household perspective that have led to the observed poverty decline.

Four main findings are important to highlight. First, increase in labor earnings—which was most rapid among those in non-agricultural wage/salaried employment but also occurred in agriculture— was a major factor in reducing poverty. This was complemented by workers shifting out
. & Olurinola, I. O. (2014). Determinants of Labor Force Participation in Nigeria: The Influence of Household Structure. _Journal of Economics and Development Studies_ , Vol. 2, No. 2, pp. 169-19

- Fay, D. and Frese, M. (2001). The concept of personal initiative: An overview of validity studies. _Hum. Perform. 14,_ 97–124

- Fernandez, R. and Fogli, A. (2005.) Culture: an Empirical Investigation of Beliefs, Work, and Fertility. NBER Working Paper No. 11268.

- Fortin, N. M. (2005). Gender role attitudes and the labor-market outcomes of women across oecd countries _. Oxford review of Economic Policy, 21_ (3):416–438.

- Friedman, W., Kremer, M., Miguel, E. and Thornton, R. (2011). “Education as Liberation?” _Economica_ , https://doi.org/10.1111/ecca.12168

- Ghana Statistical Service- GSS (2014), Ghana Living Standards Survey, Wave 6, GLSS 6, Labor Force Report

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- Giuliano, P. (2004). On the Determinants of Living Arrangements in Western Europe: Does Cultural Origin Matter? Unpublished paper

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intended for sale. To some extent, these shifts may be expected, since the end-of-season survey was (for the most part) conducted after the main harvest. However, the magnitude of labor reallocations is still surprising, considering that farmers also grow other crops which follow a somewhat different production calendar. In addition, the bottom panel of Table 4 shows that household members are more likely to report some of their products (i.e. maize, goats and chickens) as being intended for sale at the end rather than at the beginning of the season.<sup>30</sup> This change in the self-reported intended use of output for specific products contributes to the increase in the share of farmers producing for sale over the course of the agricultural season, though, clearly, it not as important a factor as farmers’ labor reallocation across products.

**Table 4: Changes in labor allocation across products and their intended use over the season, Malawi**

|**Start-of-season**|**End-of-season**|**N(combined)**|
|---|---|---|
|_Products worked on during last 7 days_|||
|Any crop<br>0.90|0.51***|386|
|(0.02)|(0.04)||
|Maize<br>0.79|0.07***|386|
|(0.03)|(0.02)||
|Irish potato<br>0.09|0.10|386|
|(0.02)|(0.02)||
|Pigeon pea<br>0.43|0.21***|386|
|(0.04)|(0.03)||
|Any livestock<br>0.46|0.73***|386|
|(0.
Policy Research Working Paper 5945

# **Abstract**

The paper investigates the relation between social capital and life satisfaction focusing on the distinction between bonding and bridging. Using the latest version of the combined World and European Values Surveys, the authors first address the question of measurement of social capital by means of a multi-step factor analysis. Through this procedure, they nd that proxies typically used for social capital tend to polarize around two dimensions interpreted as bonding and bridging. These two dimensions are in fact associated with a single latent variable with opposite signs suggesting that they describe two sides of the same latent variable rather than two independent latent variables. The authors call this latent variable the l _ocus of socializing_ and use it to explore the relation between social capital and life satisfaction across world citizens and across groups of similar countries. The results indicate that people with extreme bonding or bridging attitudes are less happy than people with more balanced attitudes. Unlike the literature on social capital and economic growth that finds bridging attitudes more desirable than bonding attitudes, they nd that bonding attitudes are at least as important as bridging attitudes for life satisfaction. This suggests that the social capital dimensions important for economic growth may not necessarily coincide with the social capital dimensions important for life satisfaction.

This paper is a product of the Economic Policy, Poverty and Gender Unit, Middle East and North Africa 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 author may be contacted at pverme@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
# **5. RESULTS**

# **5.1. TRADE SPECIALIZATION**

First, we examine the outcomes when only financial sector development, proxied by the private credit to GDP ratio, is considered. The association between financial sector development with both sector-level external finance dependence (������ ) and asset tangibility (��� ) are included in the regression. The interaction terms with these two sector-specific requirements capture different mechanisms. The interaction term with ������ captures how industries highly reliant on external financing benefit more from financial sector development since financing from sources outside the firm becomes less costly relative to the firm’s own funds. The interaction term with ��� reflects the agency problem and the preference towards lending to firms that have tangible (i.e,. physical) assets to offer as collateral.

Table 3 display estimates for equation (2) using the share of exports per sector as the dependent variable. Results for trade specialization are shown using data from both the BACI and the EDD. The BACI data contains many more MENA countries than the EDD data set. Results in columns (1) and (3) yield similar results to Beck (2003), a significant correlation is found between sectorlevel external finance dependence and a country’s financial sector development. The interpretation being that for a sector with a given level of external finance dependence, the share of exports from that sector is higher in countries where the financial sector is more developed. This result holds irrespective of the export data source, though the effect is much smaller using BACI data than the EDD, possibly reflecting the different country and temporal coverage of the data sets. Results from columns (2) and (4) are also consistent with Hur, Raj, and Riyanto’s (2006) study, which examines both sector level external finance dependence and asset tangibility.

The summary statistics in Table 3 (lower section) shows that sector-level dependencies and private credit to
available since the 1980s and data is best only for the most recent decades, which saw only limited sovereign defaults. Additionally, for some exercises the PIP require further exclusions, as we explain in the relevant sections below. The analyses of proxies of multi-dimensional poverty rely on longer annual data series that often start in the 1960s. Our analysis of per capita output has the most complete data coverage starting in 1900. However, the sample changes over time owing to waves of independence along with any gaps in the per capita GDP data series from the Maddison Project. Lastly, it is important to</mark>

> 4 <mark>This in itself is somewhat problematic, since Argentina had been in default for more than half of the twenty years prior to the 2001 default. We provide stylized facts using a wider, though still not representative sample. Note also that some related literature exists considering the political economy of inflation inducing decisions and the policies’ differential impact: Albanesi (2007) argues that low-income households are more negatively affected by inflation. As inequality increases the bargaining power of low-income households diminishes, and the government follows policy decisions that are less likely to favor the group with diminished bargaining power, thus raising equilibrium inflation.</mark>

3
of cellular “airtime” (a simple precursor to mobile money) from members of their social network, especially those with whom they had already established reciprocal relationships.

> 13 The reciprocity motive for participation in informal financial networks appears to be a pervasive one in the developing world. For example, using historical loan contract data from low-income rural villages in China in the 1930s, Brandt and Hosios (2010) show that informal loans were predominantly used for consumption purposes and that a large share of these loans carried no interest rate. They argue that these arrangements should be interpreted as “long-term reciprocal insurance or patronage relationships between households.”

6
state-owned company, the auditor general carries out the external audit, which is contracted out to a reputable independent audit firm.

**Table 9. Utility management index of utilities in Kenya and comparators,** 2015

||Senegal<br>SENELEC|Kenya<br>Kenya Po|Tanzania <br>wTANESCO|Uganda<br> UMEME|International<br>benchmark|
|---|---|---|---|---|---|
|**Utility Management**|**56%**|**80%**|**65%**|**76%**|64%|
|_Financial Discipline_|_57%_|_76%_|_64%_|_77%_|59%|
|_Human Resource_|_57%_|_64%_|_71%_|_71%_|62%|
|_Information and Technology_|_53%_|_100%_|_60%_|_80%_|71%|

Note: Scores based on index developed for the Rethinking Power Sector Reform Project. For more details go to project website at http://www.esmap.org/rethinking_power_sector_reform KPLC has a highly competent and technically qualified staff, putting Kenya’s scores for human resources policies in line with the average for the global benchmark group (table 9). Although salaries are fixed by the Salaries and Remuneration Commission (as it is state-owned company), KPLC is considered an attractive employer in Kenya. Managerial autonomy with respect to staff decisions remains somewhat restricted. In 2018, KPLC had 11,270 staff, of whom 32 percent had short-term or contract status. About 20 percent of the staff are women. The utility runs its own training school, open to all Kenyans, from which it hires part of its technical staff. In addition to hiring graduates of the training school, staff recruitment is done by internal advertisement,
on rice farming. Since HIES 2014 does not include a comparable agricultural module, we cannot construct a 2014-16 panel of EAs for the agricultural production data along the lines of our consumption expenditure data. Instead, our analysis of the impact of the Ebola outbreak on farm labor and production outcomes is purely cross-sectional.

# 2.2 Mortality during the Ebola Outbreak

On 30 March 2014, Liberia confirmed its first two cases of Ebola virus disease in Foya, Lofa County. By June the first deaths from Ebola occurred in Monrovia when seven patients died from the disease. Although, at the time, only 16 cases were reported in Liberia in total, with the urbanization of the disease the outbreak quickly spiraled out of control, peaking in the first quarter of 2015. By June 2016, when Liberia was (provisionally) declared Ebola-free, 10,678 people had been infected with Ebola, and over 4,800 had died.

Ebola-related burial data obtained from the Ministry of Health up to December 2015 indicate 4,621 total casualties, corresponding reasonably closely to the official figures. Of these deaths, 2,221 were matched to rural areas.<sup>8</sup> In rural Liberia, adult males were the main group of mortal victims from Ebola, but close to a third of the fatalities were under-fives (8%) and adults over 65 (24%) (See table A1.2 in Appendix 1).

> 8 The rural classification was done for georeferenced burials (4257/4621) at the locality level using the official cutoff population of < 2,000 as used in the HIES.

6
---|
|||Multilateral<br>debt|Official<br>bilateral debt|Private<br>and<br>other<br>external debt|Domestic<br>debt|
|**_Full sample_**<br>**_(21)_**|65|38|20|8|34|
|**_PPG_**<br>**_debt_**<br>**_above_**<br>**_60%_**<br>**_of GDP (11)_**|99|31|12|15|43|
|**_PPG_**<br>**_debt_**<br>**_below_**<br>**_60%_**<br>**_of GDP (10)_**|28|46|28|1|25|

_All data are means._ _<u>Source: DSAs</u>_ For external debt, there are only data in the DSAs on the breakdown by type of creditor for 21 SIDS. Table 6 shows the breakdown of public debt into external and domestic and, for external debt, by type of creditor, for these SIDS. These countries are divided into two categories in the

> 19 Data from the IMF World Economic Outlook database, April 2023. The average for the SIDS excludes Palau because there are no data on this indicator for Palau in the WEO database. The PPG debt shown in table 5 (which is taken from IMF country reports) is slightly higher than general government debt because it includes government guarantees. The average PPG debt to GDP in 2022 for the 34 SIDS shown in table 5 was 67 percent. There are no data on PPG debt to GDP in the WEO database.

20
Relations: An Analysis of Village Survey Data in East India", _Economic and Political Weekly_ , 13: 367-84.

- [20] Bardhan, P. and A. Rudra (1981), “Types of Labour Attachment in Agriculture: Results of a Survey in West bengal, 1979", _Oxford Bulletin of Economics and Statistics_ , 43: 89-111.

- [21] Barr, A., M. Dekker, and M. Fafchamps (2012), “Who Shares Risk with Whom under Different Enforcement Mechanisms", _Economic Development and Cultural Change_ , 60(4): 677-704.

- [22] Barr, A. and G. Genicot (2007), “Risk Sharing, Commitment and Information: An Experimental Analysis", _Journal of the European Economic Association_ , 6(6): 11511185.

- [23] Barro, R. (1974), “Are Government Bonds Net Wealth?”, _Journal of Political Economy_ , 82(6): 1095-1117.

- [24] Battaglia, M., S. Gulesci and A. Madestam (2019), “Repayment Flexibility and Risk Taking: Experimental Evidence from Credit Contracts", working paper.

28
database that covers a large number of countries over a long time period and includes a wide range of measures of financial integration. This allowed us to examine how the relationship has changed over time and across countries. Our results indicate that, consistent with theoretical predictions, a higher degree of financial integration is associated with a lower sensitivity of consumption to income over time. We also provide a discussion of several alternative interpretations of changes in the sensitivity of consumption and income over time.

These results point to two areas for future research. First, country-specific features can affect the relationship between international financial integration and the sensitivity of consumption to income. For example, our simple robustness analysis suggests that trade integration and financial sector development can affect this relationship. It would be useful to conduct a comprehensive study of the linkages between financial integration and trade and financial development, and how these linkages endogenously affect the proportion of rule-of-thumb agents in an economy, using a framework similar to Davis (2014). Second, it would be useful to study how the changes in the sensitivity of consumption to income affect the transmission of international business cycles using the benchmark statistics we provide here.

# References

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- [2] Bacchetta, P. and S. Gerlach. 1997. ""Consumption and credit constraints: International evidence." Journal of Monetary Economics 40(1997) 207-238.

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- [4] Bilbiie, F.O., 2008. “Limited asset markets participation, monetary policy and (inverted) aggregate demand logic.” J. Econ. Theory 140 (May (1