rafmacalaba/datause-encoder-data huggingface dataset:
# **Electoral Effects of Integrating Forced Migrants: Evidence from a Southern Country**<sup>*</sup>

Sandra V. Rozo<sup>†</sup> _⃝_ r Alejandra Quintana<sup>‡</sup> _⃝_ r Mar ́ıa Jos ́e Urbina<sup>§</sup> Originally published in the Policy Research Working Paper Series on _March 2023._ This version is updated on _February 2025._ To obtain the originally published version, please email prwp@worldbank.org.

**Keywords:** Refugees, amnesties, electoral outcomes. **JEL Classification:** D72, F02, F22, O15, R23

> *We are grateful to the editor, Pr. Angelika Rettberg, and the two anonymous referees for the constructive comments. We also thank Marco Tabellini, Mauricio Romero, Claudio Ferraz, Mushfiq Mobarak, Anna Maria Mayda, Michela Carlana, and Ekaterina Zhuravskaya for useful suggestions. We also appreciate suggestions from participants at the SEA presidential session on immigration, HUMANS LACEA Migration Meeting, EAFIT economics seminar, and the WALES conference at Georgetown University. This project was approved by the HML’s IRB in July 2022

(study protocol 2021). Pre-registered trial AEARCTR-0009806.

> †World Bank, Development Research Group. Corresponding author, e-mail: sandrarozo@worldbank.org, tel:+13109945081

- ‡Columbia University, e-mail: aq2241@tc.columbia.edu, tel:+12172501400

> §World Bank, e-mail: murbinaflorez@worldbank.org, tel:+971521034492
18 Table 9

||_90.2|-92.2|90.2|-9 1. 3'|91.4|-92.2'|
|---|---|---|---|---|---|---|
||Estimate|t-stat|Estimate|t-stat|Estimate|E-stat|
|,|__-71259_|-4.850|-13.909|4.306|4.399|-2.258|
|**(32**|0.003|0-437|0.020|1.267|-0.003|_-0.364_|
|33|0.030<br>L|1645|0.042|1.212|-0.184|-1.918|

WPC: growth rate of the quarterly wage bill: WPC': growvth rate of the quarterlv wage bill according to the PPWW norm: LTX cumulative tax liability under the PPWW scheme (cumulated from Januarv 1 of the ongoing calendar year up to the start of the quarter): EMPL: average employment in current quarter GVAPC: growth rate of quarterly real gross value added. BBPC: growth rate of quarterly real bank- borrowing.

Most important for the subject of this section are the results on the significance of the PPWW scheme. Outstanding PPWW liabilities exercised a strong negative influence over wage settements: the, coefficient is negative and highly significant both over th-e whole sample period and over the sub-samples before and after the commercial bank reforms (90.2-91.3 and 91.4-92.2). This contradicts much of the academic discussion on the PPwW (which has to date not made any formal attempt at testing the often strong conclusions on the effectiveness of the PPWW-).

The second piece of evidence is of a more qualitative nature. First of all. the firms with the most. tax arrears (type A firms) were incurring the least PPWW liabilities since they exercised more wage restraint than more profitable firms, as we sawv in Table _5._ This undermines the criticism that because of the possibility of going into tax arrears the PPWW had little impact. Not surprisingly, when asked whether removal of the PPWW scheme would lead to higher average wage levels. only 40% of type A firms answered yes and the rest no. Of the type AAA firms, on the other hand, 80% expected higher wages without the PPWW scheme. This difference is understandable given our finding of more wage restmint in type A firms: in a number of them the PPWW liabilities trigger was in fact not reached, leading them to sav that removing the trigger would not have made much of a difference. The fact that no less than 80% of type AAA respondents saw the PPWW as an effective constraint strongly suggests that the PPWW did have a moderating impact.
THE REPUBLIC OF CONGO’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE In 2008–09, the GoC designed and adopted a new Policy and Strategic Vision for the ICT sector (Cyberstrategy), a road map ushering Congo to the next stage of ICT connectivity, with the goal of becoming a regional ICT hub. In 2009, the Republic of Congo adopted an important legal and policy framework for regulation of the postal and telecommunication sectors. It is expected to expand the use of new technologies in the sector.

**Table 3. Benchmarking ICT infrastructure**

||Unit|**Republic of**|**Congo**|Resource-rich countries|
|---|---|---|---|---|
|GSM coverage|% population|**75.0**||47.7|
|Interment bandwidth|Mbps/capita|**0.29**||2.7|
|Internet|subscribers/100 people|**0.03**||0.3|
|Landline|subscribers/100 people|**0.41**||1.1|
|Mobile phone|subscribers/100 people|**35.4**||23.7|
|**Prices**(US$)|**Republic of Congo**|Without<br>submarine<br>cable|With<br>submarine<br>cable|Other developing<br>regions|
|Price of monthly mobile basket|**18.8**|11.1|13.6|9.9|
|Price of monthly fixed line basket|**—**|13.6|16.7|—|
|Price of 20-hour Internet package|**84.5**|68.0|47.3|11.0|
|Price of a 3-minute call to United States|**5.4**|2.6|1.4|2.0|
|Price of inter-Africa telephone calls, mean|**—**|0.72|0.44|n.a.|

_Source_ : Ampah and others 2009. — = data not <u>available; n.a. = not applicable</u>

# **Box 1. Congo’s mobile operators**

# _Zain_

Zain launched services as Celtel in December 1999 and was rebranded in 2008. The company’s subscriber base grew from 43,000 in December 2000 to 116,000 by December 2001 and 165,000 by December 2002. By 2007, Zain had reached 1,014,000 subscribers.

# _MTN_

Originally a Telecel subsidiary, the company that is now MTN was bought by Orascom, which rebranded it Libertis in May 2000 and sold it outright to MTN in 2005. The Libertis subscriber base grew from 22,600 in 2000 to 47,635 in September 2001, 73,438 in September 2002, and 76,544 by December 2002. When MTN bought the company, it recorded 210,000 subscribers in December 2005, which represented a 35 percent market share. By December 2007, this figure had grown to 330,000. ARPUs remained constant at $20 for both 2006 and 2007.

# _Warid Telecom_

In 2006, Warid Telecom announced that it would form a joint venture with incumbent Congo Telecom (SOTELCO). The government licensed it to offer both voice and data services. It launched in January 2008 and said it would invest $95 million over five years.

14
# Table A.1: Balance at baseline: Additional variables

||Co|ntrol (C)||Own||BAF|C - Own|C - BAF|Own - BAF|
|---|---|---|---|---|---|---|---|---|---|
||N<br>(1)|Mean/SD<br>(2)|N<br>(3)|Mean/SD<br>(4)|N<br>(5)|Mean/SD<br>(6)|Dif.<br>(7)|Dif.<br>(8)|Dif.<br>(9)|
|Poor|346|0.168<br>(0.374)|153|0.150<br>(0.359)|158|0.165<br>(0.372)|0.017|0.003|-0.014|
|Marital duration|343|7.219|153|7.288|159|7.509|-0.069|-0.291|-0.222|
|||(3.502)||(3.542)||(3.904)||||
|Has at least one son|350|0.743|156|0.744|165|0.679|-0.001|0.064|0.065|
|||(0.438)||(0.438)||(0.468)||||
|Valued concealability of FP|350|0.514<br>(0.501)|156|0.474<br>(0.501)|165|0.467<br>(0.500)|0.040|0.048|0.008|
|Found FP embarrassing to use|349|0.367<br>(0.483)|154|0.377<br>(0.486)|164|0.293<br>(0.456)|-0.010|0.074*|0.084|
|Number of close outside peers|350|0.257<br>(0.493)|156|0.250<br>(0.477)|165|0.279<br>(0.513)|0.007|-0.022|-0.029|
|Lack of close peers in village that use FP<sup>a</sup>|225|0.733<br>(0.443)|99|0.717<br>(0.453)|103|0.670<br>(0.473)|0.016|0.063|0.047|
|Last visit to any FP clinic was|338|0.263|155|0.284|162|0.278|-0.021|-0.014|0.006|
|with husband or MIL||(0.441)||(0.452)||(0.449)||||
|F-test of joint signifcance: p-value|||||||0.731|0.429|0.533|
|F-test: Observations|||||||314|317|199|

_Notes:_ Standard deviations (SD) are in parentheses. BAF denotes Bring-a-Friend, FP denotes family planning, and MIL denotes mother-in-law.<sup>a</sup> indicates that the variable is conditional on having at least one close peer at baseline. Variable definitions are in Online Appendix.<sup>_∗_</sup> _p <_ 0 _._ 1,<sup>_∗∗_</sup> _p <_ 0 _._ 05,<sup>_∗∗∗_</sup> _p <_ 0 _._ 01
for selected crops. The shadow price is negative for lucerne because the sales price (and hence VMP) for this fodder crop is insufficient to recoup the costs of irrigation<sup>21</sup> .

We matched the estimated crop-water use coefficients and shadow values to the crop categories in the CGE model – using similar crops in cases where the regression results were unavailable or insignificant. For example, the shadow prices of potatoes and wheat were applied to all vegetables and winter crops, respectively. Furthermore, since only national experimental data was available, the same coefficients were applied in all WMAs. However, region-specific yields for each crop were used to estimate water demand. This was multiplied by the shadow price, which is measured per hectare of land, in order to calculate the total shadow value of production for different crops in each region. This was subtracted from the capital value-added for each crop reported in national accounts and the 2002 Census of Commercial Agriculture. Irrigated water therefore appears as a factor of production in the CGE model and is used exclusively by irrigated agricultural sectors. The returns to the irrigated water factor (i.e., the shadow price) are distributed to higher-income rural households according to their ownership of the returns to commercial agricultural land. The government also charges a fixed raw water tariff that vary by WMA depending on what supply schemes are providing water (Figure 3 used the 2002 average charge of R0.02/m<sup>3</sup> reported in Hassan and Matlanyani (2004)).

# 3.2.6 _Nonagricultural water use and distribution system_

Although the model pays particular attention to agriculture and irrigated water, it also captures industrial and domestic water use. Unlike irrigated water, the provision of nonagricultural water takes place via the water distribution system. In other words, it is treated as an intermediate input and not as factor of production (as was the case with irrigation water). Moreover, the water distribution system charges different tariff rates to different sectors or users, including rural and urban households, industrial users, and the mining and energy sectors (DWAF, 2002-07). However, to simplify the system, the CGE model only distinguishes between two groups: (i) heavy industry and (ii) light industry

> 21 There may be a risk premium associated with ensuring minimum levels of supply. This may explain why farmers are willing irrigate lucerne despite its negative VMP (i.e., irrigation provides a low-cost form of insurance against rainfall variability).

20
the high income countries. Hopefully, this will be due more to continued strong growth in developing countries than to low and stagnant growth in the high-income countries. The reserve currency countries, in particular, will likely face a declining share. For Japan, the UK and some countries in the Eurozone, zero or negative population growth is one factor – combined with an aging population. In the United States, fiscal retrenchment both over the medium and longer term (e.g., social security and old age health expenditures) may pose a drag on growth.

The World Bank recently produced a report that looked at longer term trends in economic growth.<sup>30</sup> The baseline scenarios on a country-by-country basis reveal the shifting pattern of economic power in the coming decades. China is likely to overtake the United States in terms of nominal GDP, while India is likely to surpass first the United Kingdom and then Japan (figures 1(a) and (b)) by 2022.

**Figures 1(a) and (b):  The Global Economy in 2025—Major MICs and Reserve Currency Countries** **<u>(In nominal US dollars, market exchange rates)</u>**

<!-- Start of picture text --> $ trillions $ trillions<br>50 18<br>China<br>45 16<br>w/ appreciation (see note)<br>40<br>14<br>35<br>12 India<br>30<br>10<br>25 United<br>20 States 8 Japan<br>15 6<br>10 China 4 United<br>5 appreciation)(no 2 Kingdom<br>0<br>0<br>2009 2011 2013 2015 2017 2019 2021 2023 2025<br>2009 2011 2013 2015 2017 2019 2021 2023 2025<br><!-- End of picture text --> Source: Reproduced from World Bank (2011).

Note: Real GDP growth from 2010 onward is based on forecasts from the baseline scenario of World Bank (2011). Inflation is assumed to be constant at 0 percent for Japan, 2 percent for the United States, 4 percent for both China and the United Kingdom, and 70 percent for India. Exchange rate appreciation, relative to the U.S. dollar, is assumed to be constant at 0 percent for China (no appreciation case), 2 percent for Japan, and 3 percent for China (appreciation case).

The implication is that the future of the current international monetary order will be even more out of line with the international real economy order. There is a clear rationale for trade and finance to be denominated in the currency of the country that dominates the global economy in terms of its weight in the global economy. Already in 2009, there was a misalignment in the currency composition of

> 30 World Bank, 2011.  This was the inaugural edition of a new annual series called _Global Development Horizons_ . Also see Dailami and Masson (2009).

9
**Table 4: Robustness Checks for Different Age Ranges: All Children**

||**Bangl**<br>|**adesh**<br>|**Ind**<br>|**ia**<br>|
|---|---|---|---|---|
||Intergenerational<br>Regression Coeff<br>(IGRC)|Intergenerational<br>Correlations<br>(IGC)|Intergenerational<br>Regression Coeff<br>(IGRC)|Intergenerational<br>Correlations<br>(IGC)|
|**Biases**||**B**|**ias**||
|**16-60 Year Age group**|||||
|Father's Education|**20%**|**6%**|**11%**|**7%**|
|Mother's Education|**24%**|**4%**|**17%**|**11%**|
|Parent's Education(average)|**11%**|**4%**|**16%**|**9%**|
|**20-69 Year Age group**|||||
|Father's Education|**9%**|**4%**|**8%**|**4%**|
|Mother's Education|**11%**|**2%**|**18%**|**11%**|
|Parent's Education(average)|**-2%**|**-2%**|**12%**|**7%**|
|**13-50 Year Age group**|||||
|Father's Education|**31%**|**11%**|**14%**|**10%**|
|Mother's Education|**34%**|**7%**|**21%**|**12%**|
|Parent's Education(average)|**24%**|**6%**|**16%**|**10%**|

NOTES: (1) Bias is defined as [(Estimate from Full Sample – Estimate from Coresident Sample) *100] / Estimate from Coresident Sample (2) All of the Bias Estimates are Significant at the 5 Percent or Lower Level.

**Table 5: Robustness Checks for Different Age Ranges: Father-Son, and Mother-Daughter**

||**Ba**|**Bia**<br>**ngladesh**|**ses**|**India**|
|---|---|---|---|---|
||Father-Son|Mother-Daughter|Father-Son|Mother-Daughter|
|**16-60 Year Age group**|||||
|Intergenerational Regression Coeff. (IGRC)|**22%**|**32%**|**6%**|**16%**|
|IntergenerationalCorrelations(IGC)|**9%**|**4%**|**2%**|**7%**|
|**20-69 Year Age group**|||||
|Intergenerational Regression Coeff. (IGRC)|**15%**|**18%**|**6%**|**7%**|
|Intergenerational Correlations(IGC)|**6%**|**6%**|**2%**|**4%**|
|**13-50 Year Age group**|||||
|Intergenerational Regression Coeff. (IGRC)|**30%**|**46%**|**7%**|**22%**|
|Intergenerational Correlations(IGC)|**9%**|**11%**|**2%**|**10%**|

NOTE: (1) Bias is defined as [(Estimate from Full Sample – Estimate from Coresident Sample) *100] / Estimate from Coresident Sample (2) All of the Bias Estimates are Significant at the 5 Percent or Lower Level
Financial Regulation and Development from the policy change in Ethiopia and a variety of robustness checks. In Section 3, we adapt the theoretical and empirical framework to the Antebellum USA study and investigate the state-level bank-tax rollover. In Section 4, we present some concluding remarks.

# **1 Theory**

## **1.1 Economic Environment**

The economy comprises a continuum of locations on the unit line, and each point is populated by a household engaging in a saving decision. The bank decides how many branches to open, _β ∈_ [0 _,_ 1], which is costly but allows it to reach a new locus and to interact with agents. If _β_ = 1, then all locations are reached, while with _β_ = 0, no branches are opened. Once a branch is installed, the bank interacts with a depositor, who chooses how much to deposit, _d ≥_ 0, given a remuneration _RD ≥_ 1. These liabilities are collected and allocated in two assets: a share in risky loans, _l ∈_ [0 _,_ 1], and the remainder in an inter-bank safe asset, _s_ = 1 _− l_ . There exist two states _σ ∈{G, B}_ : in the good state, _σ_ = _G_ , which occurs with probability _p ∈_ ( _<u>p,</u>_ 1), the bank earns on risky loans a gross rate _RG >_ 1, while in the bad state, _σ_ = _B_ , which occurs with probability 1 _− p_ , the bank earns _RB ∈_ [0 _,_ 1). In contrast, the return on the safe asset is positive, deterministic, higher than the deposit rate, and lower than the expected loan return, _RS ∈_ [ _RD, pRG_ + (1 _− p_ ) _RB_ ]. Prices are given and therefore if _G_ occurs, the bank earns _RS_ on safe assets, _RG_ on the remainder, and pays _RD_ to depositors. Given the assumptions on the rates, the good state is always profitable and the bank always repays. However, if _B_ occurs, given safe asset choice _s_ and limited liability, the bank pays the minimum between the deposit rate _RD ≥_ 1 and the return on the liquidated assets, composed by the sum of the gross return on safe assets, _sRS_ , and the return on the risky assets, (1 _− s_ ) _RB_ . This economy presents the following four stages:

1. the bank invests in financial development, deciding on the number of branches, _β_ ;

2. households reached by a branch decide how much to deposit, _d_ ; 3. the bank decides on the amount of safe assets, _s_ ; 4. the state _σ_ is realized, the bank receives loan reimbursement, repays deposits, and collects profits, and the household consumes the repaid deposits.

The timing of the game clarifies a key intuition for the role of financial regulation: given the structure of returns, the bank is not keen to hold any safe assets. Limited liability allows it to keep the profits in the good state _G_ , and to liquidate depositors with all that is collected in the bad state _B_ . Depositors anticipate this and, given the constant rates, limit their deposits in the banking system. If the bank could commit to hold an amount of safe assets always securing _RD_ , then deposits would be higher, 7
# 2-

# Health Financing in the Poor Countries: Cost Rovery or Cost Reduction

The problem of financing health services in the developing countries is currently being looked at as one of cost recovery. This is the approach taken by, in particular, the World Bank, whose activities as a pressure group are currently aimed at getting the countries to which it furnishes health assistance to undertake four policy reforms:

- _Charge users of government health facilities, especially for drugs and curative care._ "This will increase the resource available to the government health sector, allow more spending on underfunded programs, encourage better quality and more efficiency, and increase access for the poor" (who will be protected by reduced fees and will be "the principal beneficiaries of expanding resources for and improved efficiency in the government sector)." (cf. tII p. 3).

- _Provide insurance or other risk coverage,_ "in order to help mobilize resources for the health sector while simultaneously protecting households from large financial losses. A modest level of cost recovery is possible without insurance. But in the long run, insurance is necessary to relieve the government budget of the high costs of expensive curative care; governments cannot raise government hospital charges close to costs uatil insurance is widely available." (cf. El] p. 4).

- _Use nongovernment resources effectively._ "Encourage the nongovernment sector (including nonprofit groups, private physicians, pharmacists, and other heaith practitioners) to provide health services for which consumers are willing to pay. This will allow the government to focus its resources on programs that benefit whole communities rather than particular individuals...Any prohibitions or restrictions on nongovernment providers should be reviewed. Unnecessary paper work and the regulations relating to nonprofit providers should be reduced." (cf. (ll p. 5).

- _Decentralize_ government _health services._ Decentralize planning, budgeting and purchasing for government health services, particularly the services offering private benefits for which users are charged. When setting national policies and programs, use market incentives where possible to better motivate staff and allocate resources. Allow revenues to be collected and retained as close as possible to the point of service delivery. This will improve both the collection of fees and the efficiency of the service." (cf. [11 p. 6).

These reforms are expected to have a favorable impact on the solution of three essential problems, all of which are said to be due to the efforts of governments to cover the full costs of health care for everyone from gener:l public revenues:
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30