rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 10099

# **Abstract**

Situations of forced displacement create unique challenges for social cohesion because of the major disruption of social dynamics among both displaced persons and host communities. This paper uses a sequential mixed method approach to analyze the relationship between hosting displaced persons and perceptions of social cohesion in eastern Democratic Republic of Congo. First, participatory research methods in focus groups empowered participants to pro-duce a locally driven definition of social cohesion. The results from these exercises inform the quantitative assessment by dictating measurement strategies when analyzing original surveys.

Combining almost 50,000 responses to 11 cross-sectional surveys between 2017 and 2021, displacement is negatively associated with perceptions of social cohesion in aggregate. But at the individual level, those who report hosting displaced populations in their communities often have higher perceptions of social cohesion. These results are strongest among respondents who self-report hosting IDPs as opposed to refugees, but important heterogeneity across indicators, local context, and gender should guide policy meant to promote social cohesion in forced displacement.

This paper is a product of the Social Sustainability and Inclusion Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at ppham@hsph.harvard.edu.

_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
# **_Measuring Services Reform_**

In order to make the detailed information on services sector reforms in India, which was gathered for this study, amenable to quantitative analysis, we condense the information into a composite policy index for each sector. In doing so, we have been guided by a similar index compiled by the European Bank for Reconstruction and Development for countries in Central and Eastern Europe and reported in the flagship publication _Transition Report 2004_ . This approach starts from a general template of reforms necessary to achieve a desirable policy environment, which is then adapted to the specific situation of each sector.

For each services sector _k_ , the time-varying services reform index _reformkt_ ranges from 0 to a maximum score of 5. An index value of 0 corresponds to a situation where the public sector is either the only relevant provider of services or has a strong grip on private providers, and there is extremely limited scope for the market mechanism. Note that all Indian services sectors treated here fall into this highly restrictive category before the beginning of economic reforms in the early 1990s. A level of 1 indicates at least some scope for private sector participation and some liberalization of operational decisions, combined with some very limited scope for foreign participation (limited, for example, by low FDI ceilings). To qualify for an index value of 2, there must be only a limited degree of interference with operational decisions by public authorities, substantial price liberalization, and clear scope for foreign participation even if only in narrowly defined segments and as minority shareholders. Still, the state may remain a dominant actor in the sector. An index of 3 implies significant scope for private providers, including foreign ones, clear competitive pressure on the public incumbents from new entrants, and explicit possibilities for foreign equity participation. A level of 4 is equivalent to little public intervention and the freedom of operation of private providers, the possibility of majority foreign ownership, and the dominance of private sector entities. Finally, a level of 5 (not attained in any of the sectors considered here) would reflect an equal treatment of foreign and domestic providers, a full convergence of regulation with international standards and unrestricted entry into the sector. The details of how the index was constructed are presented in on-line Appendix B (attached at the end of the manuscript). The index is available for four sectors: banking, telecoms, transport and insurance for the time period 1991-2004.

15
13 50.8 and 40.8 percent.<sup>17</sup> Results suggest that finance and commodities are important channels of propations of shocks between the two blocks namely AEs and EMs. These results are consistent with Rey (2013) work on the existence of global financial cycle in asset prices, capital flows and credit growth—over and above domestic macroeconomic conditions.

# **IV.   ALTERNATIVE IDENTIFICATION SCHEMES**

As mentioned earlier, the ordering of the decomposition is chosen such as AEs are ordered first, AEs are thus deemed “more exogenous” than EMs. In other words, we impose that EMs growth shocks do not _contemporaneously_ affect AEs growth. One could argue that while there is a strong case for such choice decomposition, our results may be overly reliant on that identification strategy. In this sub-section, we present impulse responses using arguably exogenous US fiscal news (both spending and tax) and damage from natural disasters for both EMs and AEs as a source of exogenous variation for growth shocks. To generate these impulse responses, we simply augment our benchmark bi-variate VAR with either the US fiscal news or the damage from EM/AE natural disasters. Fiscal news and natural disasters are ordered first considering their arguably exogenous nature.

Results using spending and tax news in the US confirm that the spillover running AEs to EMs is (very) large. Figure 11 show on the left hand-side panel the impulse response from an US spending news based on the narrative military expenditure shock from Ramey (2011) on AE and EM growth. The impulse response confirms that the spillover from an US spending shock is very large. The elasticity of spillovers after a year running from the US (spending shock) to EM

> 17 Note that the channels are not exclusive and interact. Therefore, the sum of the relative shares is larger than one.
**_Appendix Table D1. Number of exporters of apparel to the US per country and year_**

||Ethiopia|Kenya|Madagascar|Mauritius|
|---|---|---|---|---|
|2000||||47|
|2001||||54|
|2002||||58|
|2003||||58|
|2004||||52|
|2005|14|||49|
|2006|25|79||39|
|2007|27|50|58|40|
|2008|25|30|63|31|
|2009|27|26|49|30|
|2010|25|33|36|33|
|2011|22|43|18|38|
|2012|23|48|19|45|
|2013|28|43|19|46|
|2014|36|51|23|50|
|2015|40|46|29|35|
|2016|41|43|36|35|
|2017|44|59|31||

# **D2) Export growth decomposition formula and results**

To understand the sources of aggregate growth, we decompose the change in each country’s exports to the US between year _t-k_ and year _t,_ ΔEt into the change due to increases or decreases in exports at the existing exporting firms (i.e., intensive margin), the increase due to entry of new exporting firms, and the decrease due to the exit of existing exporters. The decomposition of export growth is as follows: where ΔEt is the change in country’s export between year _t-k_ and year _t_ , C is the set of continuing exporters that are active in export markets in both _t-k_ and _t_ , E is the set of entering exporters that are active in export markets in _t_ but not in _t-k_ , and X is the set of exiting exporters that are active in export markets in _t-k_ but not in _t_ .

11
<!-- Start of picture text --> Funnel plot with pseudo 95% confidence limits<br>o ®<br>oO<br>oy @e e<br>a a e = ® ®<br><!-- End of picture text --> <!-- Start of picture text --> (e) i a |<br>= / e\: ®<br>oS e/ at ®<br>wn / @ |@ \<br>/\<br>j. x e<br>/ \ °<br>2/\<br><!-- End of picture text -->

<!-- Start of picture text --> /\<br>/\<br>/\<br>f 4 e<br>Si<br>-| (0) 1 2 3<br>hedges_g<br><!-- End of picture text -->

<!-- Start of picture text --> Funnel plot with pseudo 95% confidence limits<br>oO<br>@<br>f<br>/<br>‘ % xX) ee<br>TM e ‘ecco ® e ° $<br><!-- End of picture text --> <!-- Start of picture text --> o *<br>lee PE g00<br>Q \ ee<br>o. = ® @ 2<br>oa ff Q° \<br>i<br>P o ‘ fa}<br>i .e ® t e \<br>o/<br><!-- End of picture text --> <!-- Start of picture text --> :/ \<br>/ \<br>/ @ \<br>é ‘ e<br>~S<br>-1 -5 0 fe: 1<br>hedges_g<br><!-- End of picture text -->
but by the use of direct screening mechanisms which identify and exclude high risk borrowers in the agricultural sector. Suppose that we are nevertheless determined to ensure that credit does flow from the PFI's to these borrowers, perhaps because we feel that part of the perceived risk by the rFl's will be removed once they start interacting with these traditionally excluded borrowers, or that once these borrowers acquire credit and invest, a virtuous circle will set in. Then it seems clear that a subsidy will be needed for the PFI's, the exact extent of which will depend on what sort of a spread they will demand in ordor to lend to the target group. In this case the formuia should use the marginal cost of funds to the PFI's as a base, and then subtract a certain amo.,nt (say 2%) to determine the lending rate from the BoG to the PFI's, on condition that onlending from the PFI's will be monitored to ensure that it is indeed to the target group (otherwise the subsidy is a straightforward transfer of ;ent to the PFI's).

In the case of Ghana, the consensus is that the second of the two settings described above obtains. The "reference interest rate" formula is thus clear in principle. Of course, operationalising this in practice is not easy. If all PFI's were identical we could simply identify the marginal cost of funds. But in reality there is a range of PFI's, some of which rely primarily on savings deposits, while others take in time deposits. The clientele is segmented as between rural and urban banks. In principle, we could segrnent the PFI's into aifferent categories, but the project design did not allow for this. So, how to calculate the marginal cost of funds? One operational answer is to take a weighted average of interest rates offered on various types of deposits by the range of PFI's, the weights being the proportion of all deposits accounted for by each type (i.e. to estimate the average cost of funds). Bu. the formula needs to be monitorable and easily implementable, anJ information on deposit shares is not easily and openly available. Information on interest rates is indeed available, so that finally, practicaily, it was decided to take a simple average of the highest time deposit rate and the lowest savings deposit rate. Even this can be justified, it seems to me, on the principle of insufficient reason, since what we are really after is the 3
# 2.2 Explanatory variables

Our main explanatory variable is an index of labor regulation ( _Regs_ ). Not much is known about labor regulations in India’s retail sector. These regulations fall under the jurisdiction of the state governments and are contained in the Shops and Establishments Act (SEA). The SEA is a state legislation and contains various laws relating to working conditions of the employees. The main provisions of the Act are as follows:

- Compulsory registration of shop/establishment within thirty days of commencement of work.

- Communications of closure of the establishment within 15 days from the closing of the establishment.

- Regulation of hours of work per day and week.

- Guidelines for spread-over, rest interval, opening and closing hours, closed days, national and religious holidays, overtime work.

- Rules for employment of children, young persons and women.

- Rules for annual leave, maternity leave, sickness and casual leave, etc.

- Rules for employment and termination of service.

- Obligations of employers.

- Obligations of employees.

One concern here is whether labor laws in the SEA are actually enforced. The Enterprise survey provides valuable information on this point. Specifically, in one survey question stores were asked the following: Are labor regulations no obstacle, minor obstacle, moderate obstacle, major obstacle or very severe obstacle to the current operations of the store? Answers to the question were recorded on a 0-4 scale with a higher score implying a greater obstacle. For the full sample, 27% of the stores reported labor regulations to be a problem (minor or more). For these 27% of the stores, roughly one third find labor regulations as more than a minor problem. At the high end, 53% of the stores in West Bengal, 44% in Rajasthan, 39% in Maharashtra and 33% in Delhi report labor regulations 4
5 needs to be added domestic support to primary agriculture in non-OECD countries, which is another $7 billion in 2001 according to the GTAP database (Dimaranan and McDougall 2005, Ch.16b). These estimates are shown in row 1 of Table 1.

For market price support provided through trade measures, the GTAP database relies on applied tariff rates including preferential rates where applicable, plus export subsidy notifications by members to the WTO Secretariat (Dimaranan and McDougall 2005, Chs.16d and 16e). By contrast, the OECD relies on domestic-to-border price comparisons to capture the combined effect of all trade measures, both tariffs and such non-tariff barriers as quarantine restrictions. In Table 1 the cost to producers of having to pay higher prices for intermediate inputs that are subject to tariffs or export subsidies has been netted out of the gross benefits to downstream producers of market price support measures in the GTAP database.<sup>5</sup> For primary agriculture in OECD countries, the two market price support estimates differ substantially – $46 billion in the GTAP database compared with $139 billion in the OECD’s PSE estimate for 2001 (see first two columns of row 3 of Table 1). This is mainly because the GTAP method does not capture the protective effect of nontariff barriers (NTBs) such as Sanitary and Phyto-Sanitary (SPS) measures or other technical barriers to imports that may provide additional economic protection, in contrast to the OECD measure which is does. Such NTBs are still a major trade restriction despite GATT and WTO attempts to convert all non-tariff barriers to tariffs.<sup>6</sup> When direct subsidies are added to market price support the total support is the equivalent of a 22 percent ad valorem subsidy equivalent, whereas the comparable rate for the OECD Secretariat’s estimate is 44 percent (which is equal to its Producer Support Estimate (PSE) of 31 percent of the support-inclusive value of production). That difference between the GTAP and OECD’s rates is very consistent with a recent estimate of the trade-restrictiveness of NTBs in OECD agriculture in recent years, which suggests tariffs account for just 52 percent of the total tariff equivalent of both tariffs and NTBs (Lee, Nicita and Olarreaga 2006).

> 5 This is a way of capturing the impact on net value added by primary factors of production instead of just on the gross value of output, paralleling the difference between the concepts of effective and nominal rates of protection (Corden 1971).

> 6 Such NTBs are appropriately left out of Doha modeling analyses, since those NTBs are not part of the WTO negotiations in this round.
- Sandoval, Salvador (1993) _Social Change and labor Unrest in Brazil since 1945._ Boulder: Westview Press.

- Simanjuntak, Dr. Payaman (1995): _Trade Unionism in Indonesia_ Jakarta: Himpunan Pembina Sumberdaya.

- Sjhahir, Kartini (1993), "A Cross-National Comparative Study of Informal Sector Employment: The Case of Indonesia," _Urban Informal Sector Employment - A Cross-National Comparative Study,_ Research Institute for Regional Planning and Developments. Jakarta: The Sasakawa Peace Foundation, pp. 33-56.

- Tzannatos, Zafiris and Haneen Sayed (1995) Training and the labor Market in Indonesia: Policies for Productivity Gains and Employment Growth The World Bank, EA3HR.

- World Bank (1994) _Averting the Old Age Crisis._ Policies to Protect the Old and Promote Growth. Washington D.C.: Oxford University Press for The World Bank.

40
# **Figure 3**

# **Global Grain Stocks‐to‐Use Ration (Percent)**

<!-- Start of picture text --> 40%<br>35%<br>Including China<br>30%<br>25%<br>20%<br>15%<br>10%<br>1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010<br>Source: US Department of Agriculture 3<br><!-- End of picture text -->

# **Figure 4**

**Commodity Price Indices (Nominal, 2000=100)**

<!-- Start of picture text --> 500<br>400<br>300<br>200<br>Agriculture<br>100<br>Jan‐04 Jan‐05 Jan‐06 Jan‐07 Jan‐08 Jan‐09 Jan‐10<br>Source: World Bank 4<br><!-- End of picture text -->

**_Page 28_**
The final set of variables, related to schools is presented in column (5), that results in a further reduction of the dummy coefficient by 12 points, to a level of 77.26. There are interesting insights from some of these school variables. COMP ~~U~~ SE does not have a positive effect on the mathematics score, but COMPWEB does - recall that Vietnam does relatively better on internet connectivity compared to mere availability of computers. The presence of SCMATEDU and SCMATBUI, quality of school educational resources and quality of physical infrastructure, helps explain the gap, recall from Table 9 that Vietnam has superior endowments compared to the Dev7 countries. Table 10 shows that extra classes organized by the school (SCL ~~E~~ XTR CL) and the “systematic recording of data including teacher and student attendance and graduation rates, test results and professional development of teachers” (QUAL ~~R~~ ECORD) are also part of the story of explaining the Vietnam test score gap. Public dissemination by the school of test results (SCORE PUBLIC) has a positive coefficient, which is also one of the variables where Vietnam appears to have twice as many schools following this practice.

As we successively add variables in the regression equation, the number of observations in the regressions drops significantly due to missing values in the data set. Comparing available observable values to other variables for the dropped observations does not seem to indicate a systematic bias in this attrition. The 2012 PISA round included a so called ‘rotated’ module for the student’s questionnaire. The idea of the rotated module was to ask three additional sets of questions in a systematic division that increases the overall data available without burdening the respondents with excessively long questionnaires. The main caveat of the ‘rotated’ design is that these additional three sets of questions/variables only cover two-thirds of students each, and any combination of two sets would only cover one-third of students. Regressing on variables of the rotated modules, thus significantly reduces the sample size. The regression tables with rotated variables included can be downloaded from the github site for this paper. The lowest possible value for the Vietnam dummy in the Mathematics regression was 49.59, adding gap-decreasing variables from the second rotated module (appendix table A5 online). This relates to a 61% reduction of the Vietnam ‘gap’. The rest of the gap is explained due to effects not measured by PISA.

23
will raise the alarm when prices appear to spike. This paper‟s findings emphasize the importance of taking into account the spatial dimension and infrastructure conditions when forecasting how a price shock will be spread across the country and how it will hurt the population. The analysis also highlights that for some commodities shocks can be expected to be more homogenously spread across provinces than for others.

# **G. REFERENCES**

- Abdulai, A. (2004): _Spatial integration and price transmission in agricultural commodity markets in sub-Saharan Africa._ Chap. 7 in Commodity Market Review 2003-2004, FAO (ed), pp. 163–183. FAO, Rome, Italy.

- Alexander, C., and J. Wyeth (1994): “Cointegration and Market Integration: An Application to the Indonesian Rice Market,” _Journal of Development Studies_ , 30(2), 303–328.

- Badiane, O., and G. E. Shively (1998): “Spatial integration, transport costs, and the response of local prices to policy changes in Ghana,” _Journal of Development Economics_ , 56(2), 411–431.

- Baffes, J., and M. I. Ajwad (2001): “Identifying price linkages: a review of the literature and an application to the world market of cotton,” _Applie_ d _Economics_ , 33(1), 1927–1941.

- Banerjee, A., J. Dolado, J. W. Galbraith, and D. F. Hendry (1995): _Co-integration_ , _ErrorCorrection, and the Econometri_ c _Analysi_ s _o_ f _Non-Stationar_ y _Data_ . Oxford University Press, first edition.

- Baulch, B. (1997): “Transfer costs, spatial arbitrage, and testing for food market integration,” _American Journal of Agricultural Economics_ , 79(2), 477–487.

- Engle, R., and C. Granger (1987): “Co-integration and error correction: Representation, estimation and testing,” _Econometrica_ , 55(1), 251–276.

- Fackler, P., and B.K.Goodwin (2001): _Spatial Price Analysis._ Chap. 17 in Handbook of Agricultural Economics Vol.1, Ed. by B.Gardner and G. Rausser, pp. 971–1024. Elsevier Science, Amsterdam.

- Fossati, S. F. Lorenzo, and C. Rodriguez (2007): “Regional and International Market Integration of a Small Open Economy,” _Journal of Applied Economics_ , 10(1), 77–98.

- Goletti, F., A. Raisuddin, and N. Farid (1995): “Structural Determinants of Market Integration : the Case of Rice Markets in Bangladesh,” _Th_ e _Developin_ g _Economies_ , 33(2), 196– 198.

- Goodwin, B. K., and N. E. Piggott (2001): “Spatial Market Integration in the Presence of Threshold Effects.,” _American Journal of Agricultural Economics_ , 83(2), p302 – 317.

- Goodwin, B. K., and T. C. Schroeder (1991): “Cointegration tests and spatial price linkages in regional cattle markets,” _American Journal of Agricultural Economics_ , 73(2), p452 – 464.

22